📄 arXiv 일일 적재 — 산업 paradigm 시그널
cs.AI · cs.LG · cs.CV · cs.RO · q-bio · physics.optics · econ.GN 등 톱다운 chain 관련. codex 로 chain 매칭·새 paradigm 자동 감지.
🔭 새 패러다임 후보 (20건 — 기존 chain 밖 신호)
Enhancing In-context Panoramic Generation via Geometric-aware Pretraining
· 2026-07-09 · Vision
- 360도 파노라마 생성용 대규모 데이터셋 제시
- 깊이·기하 일관성 강화로 공간 이미지 품질 개선
- XR·디지털트윈·공간콘텐츠 제작 효율 수혜
OPSD-V: On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators
· 2026-07-09 · Vision
- 장영상 생성 열화 줄이는 온폴리시 증류
- 추론 비용 유지하며 품질·모션 개선
- 영상 AI·콘텐츠 생성 인프라 수혜
Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction
· 2026-07-09 · Vision
- 파노라마 기반 대규모 3DGS 재구성
- 360도 ERP로 데이터 취득 비용 절감
- 공간컴퓨팅·지도·자율주행 툴 수혜
LTM: Large-scale Terrain Model for Wildfire-prone Landscapes
· 2026-07-09 · Vision
- 노후 DEM+이미지로 저비용 3D 지형 복원
- 특징매칭 제거해 실시간 재난 대응 가능
- 산불·보험·드론 매핑 SW 수혜 신호
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
· 2026-07-09 · cs.CL
- 재귀형 멀티에이전트 웹리서치 구조 제안
- 깊이·범위 동시 확장으로 검색 자동화 고도화
- AI 리서치툴·엔터프라이즈 에이전트 수혜
SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets
· 2026-07-09 · AI
- 에너지 시장용 물리제약 AI 평가벤치 제안
- RL 에이전트의 효용-안전 트레이드오프 검증
- 분산전력·가상발전소 신뢰성 SW 수혜
Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
· 2026-07-09 · AI
- 장기 에이전트용 능동 메모리 개입 구조
- 검색보다 선택적 리마인더가 성능 개선
- AI 에이전트 인프라·워크플로우 수혜
Workflow as Knowledge: Semantic Persistence for LLM-Mediated Workflows
· 2026-07-09 · AI
- LLM 워크플로를 지식 객체로 영속화
- 추론·상태·의존성 감사 가능성 강화
- 엔터프라이즈 AI 운영·거버넌스 수혜
Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
· 2026-07-09 · AI
- 과학 아이디어 계보 추론 벤치마크 제시
- 논문 간 상속·변이 구조를 정량 평가
- AI 연구 자동화·R&D 툴 수혜 신호
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
· 2026-07-08 · ML
- LLM 에이전트용 비동기 RL 안정화 기법
- 단일 rollout으로 장기 작업 학습 효율 개선
- 코딩·추론 에이전트 후훈련 인프라 수혜
QCNN with Rough Path Signature Kernels
· 2026-07-08 · quant-ph
- 양자-QCNN으로 시계열 분류 실험
- 경로 시그니처 커널을 양자회로화
- 단기 산업성보다 양자ML 기초 신호
RL Post-Training Builds Compositional Reasoning Strategies
· 2026-07-08 · AI
- RL 후학습이 새 추론전략 합성 가능성 제시
- 단순 샘플링보다 유효 구조 선택성이 핵심
- 추론 특화 학습·평가 인프라 수혜 함의
Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops
· 2026-07-08 · AI
- AI가 연구·평가 루프까지 자가개선
- 검증기·평가모델이 핵심 병목으로 부상
- 컴퓨트·붕괴 리스크가 상용화 속도 제한
SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents
· 2026-07-08 · AI
- 에이전트용 대규모 스킬 라이브러리 제시
- 출처 근거 기반으로 신뢰·유지보수성 강화
- AI 에이전트 운영 툴체인 수요 확대 신호
Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning
· 2026-07-08 · ML
- 상호 경쟁 RL로 추론 과정 간접 평가
- 두 모델 캐스케이드 추론 성능 대폭 개선
- AI 학습·추론 비용과 에이전트 구조 함의
Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass
· 2026-07-08 · cs.DB
- LLM이 DB 파일 포맷 리더를 자동 생성
- JDBC/ODBC 우회로 분석 처리량 최대 27배
- Arrow·DuckDB·GPU 분석 스택 수혜 가능
Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning
· 2026-07-08 · cs.CL
- 구조 토큰 기반 과학 추론 모델 제시
- 단백질·분자·결정 물성 예측 동시 개선
- 바이오·화학·소재 R&D 자동화 수혜
PIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation
· 2026-07-07 · Vision
- 개인 취향 반영 이미지 생성 평가 벤치마크
- 심리·인구통계 프로필로 선호 데이터 확장
- 광고·커머스·콘텐츠 개인화 툴 수혜
Pitwall: Faithful Natural-Language Race-Strategy Briefings from a Calibrated Real-Time Monte Carlo Engine
· 2026-07-07 · cs.CL
- 실시간 스포츠 상태 기반 검증형 생성 시스템
- 몬테카를로 엔진과 LLM 결합 운영 사례
- 방송·베팅·스포츠 데이터 자동화 수혜
RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models
· 2026-07-07 · AI
- 실세계 다변량 시계열 1420억 포인트 공개
- 합성데이터 대비 TSFM 일반화 성능 개선
- 산업 예측·운영 AI 데이터 인프라 수혜
🔗 기존 chain 매칭 논문 30건
- physical-ai-vlm LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models 2026-07-09
- physical-ai-vlm ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device 2026-07-09
- physical-ai-vlm Wat3R: Underwater 3D Geometry Learning without Annotations 2026-07-09
- ai-substrate BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression 2026-07-09
- physical-ai-vlm Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference 2026-07-09
- physical-ai-vlm ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation 2026-07-09
- physical-ai-vlm When Structured Sparse Autoencoders Learn Consistent Concepts Across Modalities 2026-07-09
- ai-substrate UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing 2026-07-09
- physical-ai-vlm Multi-Modal, Multi-Environment Machine Teaching for Robust Reward Learning 2026-07-09
- physical-ai-vlm Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction 2026-07-09
- ai-substrate The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs 2026-07-09
- physical-ai-vlm AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding 2026-07-09
- ai-substrate SLORR: Simple and Efficient In-Training Low-Rank Regularization 2026-07-09
- physical-ai-vlm OpenCoF: Learning to Reason Through Video Generation 2026-07-09
- physical-ai-vlm Dual Latent Memory in Vision-Language-Action Models for Robotic Manipulation 2026-07-08
- physical-ai-vlm Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence 2026-07-08
- physical-ai-vlm MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models 2026-07-08
- cpo-photonics Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization 2026-07-08
- ai-substrate The Key to Going Linear: Analysis-Driven Transformer Linearization 2026-07-08
- physical-ai-vlm HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models 2026-07-08
- physical-ai-vlm Creativity from Friction: Human-AI Interaction for Exploratory Structural Design 2026-07-08
- physical-ai-vlm CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis 2026-07-08
- ai-substrate Co-LMLM: Continuous-Query Limited Memory Language Models 2026-07-08
- physical-ai-vlm Analysis-by-Proxy: Localization Signals in VLMs Operating as Condition Encoders 2026-07-07
- physical-ai-vlm EgoPolice: A Benchmark for Egocentric Video Understanding in High-Stakes Police Body-Worn Camera Footage 2026-07-07
- physical-ai-vlm A VLM-Enhanced Framework for Comprehensive Traffic Sign Condition Assessment Integrating Daytime Visual Performance and Nighttime Retroreflectivity Evaluation 2026-07-07
- physical-ai-vlm Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles 2026-07-07
- physical-ai-vlm Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation 2026-07-07
- physical-ai-vlm CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models 2026-07-07
- physical-ai-vlm MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation 2026-07-07
A Comparative Review of Methods to Create a Composite Index for Sustainable and Inclusive Wellbeing
Societal goals need to shift from over-reliance on gross domestic product (GDP) to broader aspects of sustainable and inclusive wellbeing (SIW). However, defining SIW and eventually measuring it with a single number is problematic because it involves many subjective and objective contributors that c…
Ricardo da Silva Vieira, Mario Biggeri, Peter Benczur, Robert Costanza, Joseph Eastoe, Tuuli Hirvilammi, Ida Kubiszewski… · 📄 PDF
Sharing economy in the era of full automation: Evidence from autonomous vehicle on-demand mobility services
The digital age has facilitated the sharing of underutilized assets. This paper focuses on privately owned autonomous vehicles (AVs), a unique class of robots that can move independently and provide transportation services. When not in personal use, private AV owners can lease their vehicles to a pl…
Xiaoyan Wang, Kenan Zhang, Yaochen Ma · 📄 PDF
Directional AI Advice: Experimental Evidence from Healthcare
Generative AI is fast becoming the first place people turn for expert advice. The advice it provides can be directional rather than neutral, shaped in part by the choices of its designers and regulators. When clients consult AI before meeting an expert, they carry this directional advice into a rela…
Yuyu Chen, Hongbin Li, Lingsheng Meng, Xinyao Qiu, Qingxu Yang · 📄 PDF
Measuring Consumption with Credit Card Data: Benchmarking and Beyond
We introduce a novel monthly county-level consumption dataset constructed from spending data on over 350 million credit cards in the Federal Reserve's Y-14M reports, covering over 3,000 U.S. counties since 2014. We first show that the data closely approximate traditional consumption measures, explai…
Aditya Aladangady, Ricardo Duque Gabriel, Carlo Wix · 📄 PDF
Multiband topological group-velocity control from slow light to light stopping
We introduce next-nearest-neighbor (NNN) couplings into a Harper--Hofstadter photonic lattice to establish a long-range topological photonic platform for group-velocity engineering. We show that the NNN couplings not only open a previously closed band gap but also flatten the dispersion of the edge …
Junhao Yang, Jiarui Wang, Jingyu Liu, Shirong Lin, Xinyuan Qi · 📄 PDF
Nyquist-Sampled Time-Domain Adjoint FDTD for Memory-Efficient Broadband Nanophotonic Inverse Design
Adjoint optimization is a cornerstone of broadband nanophotonic inverse design, but conventional time-domain implementations face a severe memory bottleneck because they retain forward-field histories at every finite-difference time-domain (FDTD) time step. Here, we show that this full time-step sto…
Mingyu Park, Owen D. Miller, Haejun Chung · 📄 PDF
Nanosecond Pulsed-Laser Treatment Couples Chloride Removal with Oxide Transformation in Salt-Corroded Carbon Steel
Maintaining carbon steel in marine environments requires surface treatments capable of simultaneously removing corrosion products and chloride contaminants whilst modifying the residual oxide layer. In this study, salt-contaminated SS400 carbon steel was treated using a Q-switched pulsed fibre laser…
Youichi Ishikawa, Yoshitaka Okuyama, Daishi Fujita · 📄 PDF
Ion-Implanted Silicon Nanoregions Enable Ultra-Low-Loss Trimming of Cladded Photonic Integrated Circuits
Photonic integrated circuits (PICs) have emerged as a key platform for information processing, including optical communication and computing. As PIC complexity increases, fabrication-induced response deviations accumulate, making post-fabrication trimming critical for unlocking their full potential.…
Zhongyu Tang, Shabnam Taheriniya, Seongmin Jo, Xinyu Ma, Akhil Varri, Anna P. Ovvyan, Vincent Spreter, Liam McRae, Xians… · 📄 PDF
Anomalous Reflection of Caustic Spin-Wave Beams in a Magnonic Waveguide
Reflection of waves at interfaces is conventionally governed by Snell's law, which follows from conservation of momentum parallel to the interface. Here we show experimentally that caustic spin-wave beams in anisotropic media obey a fundamentally different reflection mechanism. Applying time-resolve…
Franz Vilsmeier, Christian Back · 📄 PDF
Inverse-designed meta processing units for multi-task near-field photonic computing
Integrated photonic neural networks require optical operators that are simultaneously compact, matrix-general and compatible with task-level reconfigurability. Here we introduce a meta processing unit (MPU), an inverse-designed near-field photonic device that implements local complex matrix transfor…
Chu Wu, Zeyu Cai, Songtao Yang, Ruoyu Shen, Yinan Zhao, Haiou Zhang, Wei Chu, Xing Lin · 📄 PDF
Joint Discrete-Continuous Flow Matching for Open-Vocabulary Inverse Design of Multilayer Optical Coatings
Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training time, and continuous variables are discretized into sequence tokens. Multilayer optical coatings are an industrially important instance, coupling mat…
Zhiyi Li, Yuheng Jin, Yidan Huang, Nan Chen, Hongyan Fu, Yikun Bu · 📄 PDF
Doubly resonant enhancement of second-harmonic generation with in-plane phase matching in plasmonic metasurfaces on an AlInP slab waveguide
Nonlinear metasurfaces have attracted significant interest by offering the possibility to circumvent conventional phase-matching requirements of bulk nonlinear crystals, opening the way to efficient frequency conversion over ultrashort propagation distances. Here, we experimentally demonstrate metas…
Timo Stolt, Huayu Bai, Seyed Ahmad Shahahmadi, Jani Oksanen, Andriy Shevchenko, Radoslaw Kolkowski · 📄 PDF
Optimal slit width for high-precision orbital angular momentum measurement using angular double-slit interferometry
We demonstrate an optimization of angular double-slit interferometry for accurate measurement of orbital angular momentum (OAM) of vortex beams. By scanning the dynamic double slits, the topological charge (TC) magnitude is directly determined from the oscillation frequency of the on-axis intensity.…
Yu Jian, Xin Wang, Jiyang Zhang, Tao Chen, Manpeng Chang, Chen Liu, Weimin Wang · 📄 PDF
Broadband silicon photonic phase shifters driven by gradient optical forces
While initially deployed for optical interconnects, silicon photonics is increasingly being explored as a hardware platform for programmable optical systems, including linear optical processors, neuromorphic photonic networks, quantum photonic circuits and multiplexed sensor arrays. Common to most e…
Guillermo Arregui, Sander Jæger Linde, Magnus Vejby Nielsen, Bingrui Lu, Nikolaj B. Hougs, Babak Vosoughi Lahijani, Søre… · 📄 PDF
Intracellular luminescence thermometry: A story of disagreement, trust, and hope
Intracellular luminescence thermometry has long promised to reveal how heat is generated, dissipated, and regulated inside living cells. Yet, despite substantial progress, the field remains shaped by disagreement over the magnitude and physical plausibility of reported intracellular temperature grad…
Araceli de Aquino Samper, Liyan Ming, Daniel Jaque, Riccardo Marin · 📄 PDF
Low-latency FPGA-based electronic control system for fast preparation of defect-free atom arrays
The scalability of neutral atom quantum computing demands integrated electronic control systems with low latency, modular architecture, and real-time feedback capability. Here, we present an FPGA-based electronic control system that eliminates the PC from the feedback loop, integrating photon counti…
Ya-Dong Hu, Dong-Qi Ma, Tian-Yang Zhang, Liang Chen, Yi-Chen Zhang, Xiao-Kang Zhong, Wen-Yi Zhu, Hong-Jie Fan, Qing-Xuan… · 📄 PDF
Asymmetric high-harmonic generation from subwavelength bianisotropic resonators
High-harmonic generation (HHG) enables attosecond light pulses and table-top sources of coherent extreme-ultraviolet and soft X-ray radiation. Although HHG has long been associated with gases and plasma, nanostructured solids are emerging as new alternative sources enabling both the enhancement and …
Albert Mathew, Piyush Jangid, Rebecca Aschwanden, Yves Koppeler, Thomas Zentgraf, Sergey Kruk · 📄 PDF
DrugGen 2: A disease-aware language model for enhancing drug discovery
Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properties, often neglecting the influence of disease context on target behavior and therapeutic outcomes. To address this gap, we introduce DrugGen-2, a nove…
Ali Motahharynia, Mohammadreza Ghaffarzadeh-Esfahani, Mahsa Sheikholeslami, Navid Mazrouei, Matin Irajpour, Yousof Gheis… · 📄 PDF
A Theoretical Framework for Stochastic Activity Prediction in Tensor Accelerator Wallace-Tree Multipliers
Tensor accelerator multipliers burn dynamic power on every clock cycle, even when sparse operands require very little internal switching. No existing technique addresses this: zero-detection requires exactly-zero operands, structural power gating requires an idle multiplier, and offline weight selec…
Prashanthi Metku, Chandra Gandu · 📄 PDF
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation
Crossbar-based In-Memory Processing (IMP) accelerators achieve high-speed, low-power computing for deep neural networks (DNNs), but face three obstacles. First, floating-point (FP) arithmetic is incompatible with crossbars, and existing quantization schemes still require FP processors for scaling fa…
Shuo Huai, Hao Kong, Xiangzhong Luo, Shiqing Li, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu · 📄 PDF
Who Needs DRAM? We Have Fiber
The rising pressure on DRAM availability and contract pricing reflects generative AI's massive high-performance memory requirements. This pressure is heavily compounded by hyperscale data center expansion, which now consumes a significant portion of global DRAM output. In this work, we propose a new…
Hannah Atmer, Thiemo Voigt, Yuan Yao, Stefanos Kaxiras · 📄 PDF
Detecting Ladder Logic Bombs in IEC 61131-3 PLC Programs using ESBMC-PLC+: A Formal Verification Approach with Trigger Synthesis
A Ladder Logic Bomb (LLB) is malicious control logic in a Programmable Logic Controller (PLC) program that lies dormant until a trigger activates a payload to manipulate actuators, forge sensor readings, or deny operator control. We observe that real malicious logic hides inside function-block bodie…
Pierre Dantas, Lucas Cordeiro, Waldir Junior · 📄 PDF
FPGN: Redefining Ultra-Fast Programmable Gate-based Neural Acceleration with Differentiable LUTs
Achieving nanosecond-scale inference latency for deep neural networks (DNNs) has become a primary architectural concern for latency-critical applications. While Field-Programmable Gate Arrays (FPGAs) offer a promising substrate for low-latency inference, conventional FPGA accelerators remain arithme…
Jiawei Liang, Haotong Qin, Linfeng Du, Xingyu Liu, Shangkun Li, Hui Yu, Michele Magno, Xinyu Chen, Jiang Xu, Wei Zhang · 📄 PDF
ESBMC-Arduino: Closing the Deployment Gap for Formal Verification of Open-Hardware PLCs
OpenPLC, Arduino OPTA, CONTROLLINO, and Industrial Shields M-Duino bring IEC 61131-3 to low-cost microcontrollers used in real automation and industrial control system (ICS) security research. Existing open-source verifiers for IEC 61131-3, including ESBMC-PLC, prove safety over an abstract scan-cyc…
Pierre Dantas, Lucas Cordeiro, Waldir Junior · 📄 PDF
Input-Constrained Spatiotemporal Tubes for Safe Navigation of Unknown Euler-Lagrange Systems in Dynamic Environments
Safe navigation in dynamic environments is challenging when system dynamics are unknown and actuator inputs are limited. Existing methods either rely on accurate models, require online optimization, or do not explicitly account for input constraints. This paper presents a real-time control framework…
Siddhartha Upadhyay, Ratnangshu Das, Pushpak Jagtap · 📄 PDF
X-ACTA: eXtended Analytic Center Tension distribution Algorithm for fixed and mobile cable-driven-parallel-robot
Steering Cable-Driven Parallel Robots (CDPRs) beyond their Wrench-Feasible Workspace (WFW) augments their capabilities in challenging scenarios such as during aggressive maneuvers or following a cable failure. In this context, although the determination of cable tensions is a well-studied topic, onl…
Domenico Dona', Vincenzo Di Paola, Alberto Trevisani, Matteo Zoppi · 📄 PDF
TFP: Temporally Conditioned Memory-Fusion Policies for Visuomotor Learning
Vision--Language--Action (VLA) policies such as $π_{0.5}$ and OpenVLA perform well on many manipulation tasks, but they are often reactive: the next action is predicted from the current observation, instruction, and proprioceptive state. This assumption breaks down in stage-dependent manipulation, w…
Yushen Liang, Yue Peng, Baosheng Jin, Tianluo Zhang, Xinyu Zhang, Shuyi Zhou, Zhuoran Chen, Xinqi Liu, Shenji Wan · 📄 PDF
INTENT: An LSTM Framework for Vehicle Intention Prediction in Intersection Scenarios with Comprehensive Ablation Analysis
Vehicle intention prediction is a pivotal aspect in the agility and safety of autonomous vehicles in all driving scenarios; if genuine enhancement of autonomous vehicles are required, we need to make them adopt human interpretation of driver's intention especially in cases that require a lot of huma…
Logine M. Zaki, Catherine M. Elias · 📄 PDF
AnyDexRT: Calibration-Free Dexterous Hand Retargeting with Few-Shot Human Guidance
Teleoperation is a key interface for controlling dexterous robotic hands and collecting demonstrations for imitation learning. Its effectiveness largely depends on kinematic retargeting, which maps operator hand motions to feasible and intuitive robot hand motions. Existing methods often require han…
Chenxi Wang, Ying Feng, Hongjie Fang, Shangning Xia, Lixin Yang, Chuan Wen, Cewu Lu · 📄 PDF
SkillPlug: Unsupervised Skill Mining for Few-Shot Adaptation in Robotic Manipulation
Learning transferable visuomotor imitation policies that generalize across diverse manipulation tasks and adapt rapidly to new tasks from only a handful of demonstrations remains challenging. Most modern policies are trained end-to-end to map observations directly to low-level actions, offering litt…
Zi-han Ding, Ziwei Wang · 📄 PDF
FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation
Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs. Compared with GPS-dependent or pre-programmed navigation, VLN supports intuitive human-machine interaction and stronger environmental adaptability, …
Xueke Zhu, Qingyan Meng, Liutao Yu, Wei Zhang, Zhengyu Ma, Huihui Zhou, Yonghong Tian · 📄 PDF
Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition
Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological taxonomies rather than uncovering shared underlying behavioral structure. This limits generalization, as personality itself is better understood as th…
Jing Jie Tan, Ban-Hoe Kwan, Danny Wee-Kiat Ng, Yan-Chai Hum, Shih-Yu Lo, Po-An Chen, Noriyuki Kawarazaki, Kosuke Takano,… · 📄 PDF
On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection
Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been shown to enhance the performance of cyber-physical systems. In this work, we focus on enabling anytime computing for deep neural networks (DNNs) that proc…
Ahmet Soyyigit, Shuochao Yao, Heechul Yun · 📄 PDF
Swapping Faces, Saving Features: A Dual-Purpose Pipeline for Pedestrian Privacy in ITS
Large-scale and diverse datasets are needed to train AI models to take real-time decisions for autonomous vehicles (AVs), an intelligent transportation system (ITS) application. Pedestrian intention and trajectory prediction are critical models used in AVs, requiring datasets involving diverse pedes…
Roba H. Farouk, Catherine M. Elias · 📄 PDF
Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
Language-conditioned manipulation requires both precise contact-rich control and robust reasoning over language, scenes, and long horizons. End-to-end Vision-Language-Action (VLA) models provide strong local visuomotor skills, but they are trained on in-distribution task trajectories and often fail …
Yixian Zhang, Huanming Zhang, Feng Gao, Xiao Li, Zhihao Liu, Chunyang Zhu, Jiaxing Qiu, Yuchen Yan, Jiyuan Liu, Wenhao T… · 📄 PDF
Early to Share, Late to Save: Synchronisation-Driven Communication Gating in Bandwidth-Constrained Cooperative VLN
Most cooperative Vision-Language Navigation (VLN) methods assume unlimited communication, not considering real-world applications where bandwidth is restricted and information efficiency is critical. We introduce \textbf{bandwidth-constrained cooperative VLN} and propose \textbf{hindsight gating}: a…
Arav Gupta, Nivedan Yakolli, Avinash Gautam · 📄 PDF
FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation
We present FabriVLA, a lightweight Vision-Language-Action model for Precise Multi-Task Manipulation. FabriVLA combines an InternVL3.5 vision-language backbone with a flow-matching action head featuring gated self-attention across action tokens and shallow VLM layer fusion for enriched spatial contex…
Shiyuan Yang, Borong Zhang, Jizheng Zhang, Zhijia Tao, Junfei Guo, Donglai Ran, Xu Bian, Qingbiao Li · 📄 PDF
A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths
As human-robot interaction rapidly spreads in numerous fields, the subject of robot acceptance gains increasing importance. Visual similarity to the human body, as occurs for humanoids, is generally not enough to ensure acceptance in physical interaction, as acceptance directly links to comfort and …
Rosanna Coccaro, Enrico Ferrentino, Antonio Parziale, Angelo Marcelli, Pasquale Chiacchio · 📄 PDF
Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups
Modern robotic perception increasingly involves large-scale geometric optimization problems distributed across multiple robots or sessions. However, existing distributed solvers often depend on brittle hand tuning and primarily target rigid body pose graphs. To address this, we present DeepCORD, a l…
Jaeho Shin, Maani Ghaffari, Yulun Tian · 📄 PDF
ContactMimic: Humanoid Object Interaction via Contact Control
Keypoint tracking alone is insufficient for object interaction tasks such as sitting on a chair, wiping a board, or pushing furniture, where the robot can reach the correct pose without making meaningful physical contact with the object. We present CONTACTMIMIC, a learning framework that tracks expl…
Xinyao Li, Xialin He, Runpei Dong, Saurabh Gupta · 📄 PDF
DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation
Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and robot embodiments. However, existing benchmarks remain limited in task and data diversity, embodime…
Yunchao Yao, Zhuxiu Xu, Tianqi Zhang, Zixian Liu, Sikai Li, Zhenyu Wei, Feng Chen, Dihong Huang, Kechang Wan, Chenyang M… · 📄 PDF
VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval
Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories. Although recent vision-language and reference-based approaches have significantly advanced this field, they often rely on text prompts, limited visual examples, or expensive feature mat…
ZhiXin Sun · 📄 PDF
Switch-Reasoner: Learn When to Think in Multitask Mixtures via Reinforcement Learning
Multimodal Large Language Models (MLLMs) often follow a fixed Think-then-Answer paradigm, which is inefficient in heterogeneous multitask settings because simple inputs may not require explicit reasoning while difficult ones can benefit substantially from it. Learning when to think is also unstable …
Yiyang Fang, Pei Fu, Jinjie Li, Jian Liang, Wenke Huang, Ruijie Luo, Shaojie Zhang, Jian Luan, Yi R. Fung, Mang Ye · 📄 PDF
Native Video-Action Pretraining for Generalizable Robot Control
The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed for digital content creation is inherently inadequate for physical environments. To bridge this gap, we present LingBot-VA 2.0, a video-action foundat…
Qihang Zhang, Lin Li, Luyao Zhang, Shuai Yang, Yiming Luo, Shuaiting Li, Ruilin Wang, Junke Wang, Jiahao Shao, Gangwei X… · 📄 PDF
Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection
The rapid advancement of generative AI has enabled the creation of highly realistic deepfake media, posing significant threats, including misinformation, digital identity theft, fraud, and manipulation of public opinion. AI-generated image (AIGI) detection is reliably challenging due to the diversit…
Kutub Uddin, Nusrat Tasnim, Awais Khan, Mohammad Umar Farooq, Khalid Malik · 📄 PDF
Multi-Resolution Feature Stem for Diabetic Retinopathy lesion segmentation
Diabetic Retinopathy (DR) is a leading cause of preventable blindness worldwide, requiring automated lesion segmentation using deep learning models for early detection and monitoring. However, DR lesions vary dramatically in size from tiny microaneurysms to large hemorrhages and exudates. This varia…
Indranil Dutta, Taehee Jeong · 📄 PDF
SAM-MT: Real-Time Interactive Multi-Target Video Segmentation
Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable performance in single-target scenarios, extending them to multi-target settings typically involves replicating the single-target processing for each indivi…
Ruiqi Shen, Chang Liu, Henghui Ding · 📄 PDF
HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales
Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unprecedented challenges to digital content forensics. Existing benchmarks primarily focus on either face-swapping or global text-to-video synthesis, o…
Wenbo Xu, Zhimin Chen, Xiaojie Liang, Hengrui Liu, Wei Lu · 📄 PDF
WaspMOT: A Benchmark for Long-Term Multi-Object Tracking of Trichogramma Wasps
Multi-object tracking (MOT) has achieved strong performance on benchmarks dominated by short video sequences. However, such datasets do not adequately evaluate long-term identity preservation, where objects must be tracked consistently over extended durations. We introduce WaspMOT, a benchmark desig…
Tomasz Stanczyk, Yuan Gao, Hardik Agarwal, Seongroo Yoon, Tiantao Zhang, Vincent Calcagno, Francois Bremond · 📄 PDF
Enhancing In-context Panoramic Generation via Geometric-aware Pretraining
In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream task-specific fine-tuning. To address the lack of large-scale, high-quality training data tailored to in-context panoramic tasks, we propose Canvas36…
Haoran Feng, Ruiyang Zhang, Longyi Zhang, Dizhe Zhang, Lu Qi · 📄 PDF
OPSD-V: On-Policy Self-Distillation for Post-Training Few-Step Autoregressive Video Generators
We propose OPSD-V, an on-policy self-distillation paradigm for post-training few-step autoregressive (AR) video diffusion models. Existing few-step AR video generators can produce long videos with low latency, but still suffer from error accumulation and weakened motion dynamics during long autoregr…
Hongyu Liu, Chun Wang, Feng Gao, Xuanhua He, Yue Ma, Ziyu Wan, Yong Zhang, Xiaoming Wei, Qifeng Chen · 📄 PDF
Geometry and Gradient-based Partitioning for Panoramic Outdoor Reconstruction
Scaling 3D Gaussian Splatting (3DGS) to large outdoor scenes is costly in both data acquisition and computation. Adopting panoramic images with equirectangular projection (ERP) can reduce capture effort via their full $360^{\circ}$ field of view, yet the resulting omnipresent visibility invalidates …
Weijian Chen, Weibo Yao, Yuhang Zhang, Xiaolin Tang, Guo Wang, Weijun Zhang, Xitong Gao, Yihao Chen, Hongde Qin, Lu Qi · 📄 PDF
LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models
Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models struggle with long-term stability. We propose LongE2V, a novel approach that leverages pre-trained video diffusion priors to jointly handle event-ba…
Cheng-De Fan, Chun-Wei Tuan Mu, Chen-Wei Chang, Chin-Yang Lin, Kun-Ru Wu, Yu-Chee Tseng, Yu-Lun Liu · 📄 PDF
ZipDepth: Bringing Lightweight Zero-Shot Monocular Depth Anywhere, on Any Device
Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational demands place them far beyond the reach of embedded and mobile platforms. Lightweight alternatives exist, but have been developed almost exclusively wi…
Fabio Tosi, Luca Bartolomei, Matteo Poggi, Stefano Mattoccia · 📄 PDF
Wat3R: Underwater 3D Geometry Learning without Annotations
Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-quality 3D annotations. Pioneering methods rely on massive dense annotations that are impractical in underwater settings. In this paper, we propose …
Jiangwei Ren, Xingyu Jiang, Zijie Song, Wei Xu, Hongkai Lin, Dingkang Liang, Xiang Bai · 📄 PDF
Federated Deep Learning for Privacy-Preserving Cardiovascular Disease Risk Prediction
Cardiovascular disease risk prediction models often rely on data from a single institution or centrally pooled datasets. Extending these models across institutions could be limited by privacy regulations and constraints on sharing patient-level data. Federated learning enables collaborative model de…
Hyunho Mo, Djura Smits, Mahlet A. Birhanu, Maarten J. G. Leening, Daniel Bos, Pim van der Harst, Esther E. Bron · 📄 PDF
Steering Neural Network Training through Interpretable Constraints Based on Partial Dependence
Over the last few years, there has been an increased interest in making machine learning models more interpretable. Although a great deal of effort goes into developing techniques for interpreting the interactions learned by a given model, fewer studies focus on assessing the quality of such explana…
Yann Claes, Pierre Geurts, Vân Anh Huynh-Thu · 📄 PDF
BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression
Large language models (LLMs) are increasingly constrained by memory capacity, weight bandwidth, and checkpoint storage during deployment. Existing low-bit compression methods mainly follow two directions. Scalar or group-wise quantization is simple and compatible with efficient low-precision kernels…
Yuantian Shao, Peisong Wang, Zhilei Liu, Chuangyi Li, Yuanteng Chen, Pengcheng Xie, Yiwu Yao, Zhihui Wei, Jian Cheng · 📄 PDF
Secure Decentralized Federated Learning via Gossip and Virtual Voting
Decentralized federated learning (DFL) removes the central server by letting nodes exchange model updates through peer-to-peer gossip, but existing gossip-based methods often lack provenance finality and resilience to Byzantine or lazy participants. Ledger-assisted federated learning (FL) improves a…
Amirhossein Taherpour, Xiaodong Wang · 📄 PDF
EdgeRefine: Privacy-Utility Balance for Graphs via Jaccard Sampling under Edge Differential Privacy
Graph Neural Networks (GNNs) have shown considerable success in learning from graph-structured data, but their use in privacy-sensitive areas remains difficult because graph structure can leak sensitive link information. To satisfy edge-level differential privacy, a common approach is to inject nois…
Wenxiu Ding, Muzhi Liu, Zheng Yan, Mingjun Wang, Yifan Zhao, Qiao Liu · 📄 PDF
Resample or Reroute? Budget-Aware Test-Time Model Selection for Large Language Models
Routing among large language models (LLMs) trades response quality against serving cost, motivated by the reported gap between deployed routers and a per-instance oracle. Recent analysis shows that test-time resampling can recover per-instance selection headroom that no single-commit router captures…
Teng-Ruei Chen · 📄 PDF
MPFlow: Learning Budgeted Max-Flow Optimization on the Lightning Network with Deep Graph Reinforcement Learning
We address liquidity placement in the Bitcoin Lightning Network (LN): given a fixed budget, which channels should a node open to maximize its routing capacity? We cast this as a budget-constrained combinatorial optimization problem on graphs, selecting $k$ edge additions that maximize $s$--$t$ max-f…
Harrison Rush, Vincent Davis, Simone Antonelli, Vikash Singh, Jesse Shrader, Emanuele Rossi · 📄 PDF
LTM: Large-scale Terrain Model for Wildfire-prone Landscapes
Accurate 3D terrain maps are essential for emergency response when assessing wildfire hazards. However, wildfire-prone regions often span vast areas where conventional reconstruction methods underperform. Airborne LiDAR systems provide high-resolution terrain data, but they are expensive and infrequ…
Xiao Fu, Yue Hu, Meida Chen, Peter Anthony Beerel, Barath Raghavan · 📄 PDF
Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems
Narrowband interference (NBI) severely degrades orthogonal frequency-division multiplexing (OFDM) systems by corrupting subcarriers and rendering classical soft demodulation ineffective. Conventional compressed-sensing (CS) mitigation exhibits high sequential latency and leaves structured, non-Gauss…
Emmanouil Kavvousanos, Francky Catthoor, Vassilis Paliouras · 📄 PDF
Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference
Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a similar capacity for adaptive "reasoning." However, transferring this capability to continuous control policies has been challenging, as directly reaso…
Chuning Zhu, Eva Xu, Jose Barreiros, Krishnan Srinivasan, Paarth Shah, Abhishek Gupta · 📄 PDF
Super Weights in LLMs and the Failure of Selective Training
Recent work identified Super Weights, individual parameters whose removal degrades model performance by orders of magnitude. We show that this degradation due to pruning Super Weights does not universally apply to all LLMs. Furthermore, if these parameters are so important, Super Weight-aware traini…
Shreyas Subramanian, Adewale Akinfaderin, Akarsha Sehwag · 📄 PDF
ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation
Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation approaches offer precise control via text and kinematic constraints, they lack the inference speed required for interacti…
Kaifeng Zhao, Mathis Petrovich, Haotian Zhang, Tingwu Wang, Siyu Tang, Davis Rempe · 📄 PDF
MulTTiPop: A Multitrack Transcription Dataset for Pop Music
We present MulTTiPop, a dataset of pop music segments and their associated multitrack MIDI recordings for the evaluation of automatic music transcription models. MulTTiPop contains 572 segments of popular music totaling 3.5 hours of audio, and contains songs from diverse genres and decades from the …
Nathan Pruyne, Benjamin Stoler, William Chen, Chien-yu Huang, Shinji Watanabe, Chris Donahue · 📄 PDF
Score Accuracy Along the Forward Diffusion Does Not Certify Numerical Stability in Diffusion Sampling
Score matching controls average error under the forward marginals, but a discretized reverse-time sampler evaluates the learned score along its own trajectory. We show that small forward-marginal error does not guarantee numerical stability. We construct a single smooth score field with arbitrarily …
Yiwei Zhou · 📄 PDF
When Structured Sparse Autoencoders Learn Consistent Concepts Across Modalities
Sparse autoencoders (SAEs) have emerged as a promising technique for mechanistic interpretability by learning a set of sparse latent features in large models, each of which encodes a distinct concept. However, in vision-language models (VLMs), vanilla SAEs struggle to learn modality-consistent conce…
Weiduo Liao, Yunqiao Yang, Ying Wei · 📄 PDF
The complexities of patient-centred conversational artificial intelligence
Consumer-facing health chatbots powered by large language models (LLMs) are increasingly used for symptom assessment. However, chatbot development and evaluation often rely on cooperative, articulate, simulated patients. We analysed 2,053 real patient-chatbot conversations and found that communicati…
João Matos, Olivia Buege, Donny Cheung, Gary S. Collins, Paula Dhiman, Nan Li, Bingyu Mao, Benjamin W. Nelson, Michail O… · 📄 PDF
UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing
As available training data approaches its physical limit, gains from Scaling Laws have begun to diminish. Consequently, improving Large Language Models (LLMs) now depends less on data expansion and more on higher-quality data utilization. However, in the context of large-scale corpora, existing refi…
Xinlong Zhao, Dongsheng Liu, Hengyu Zhao, Zixuan Fu, Zheng Wang, Jie Cai, Jie Zhou, Qiang Ma, Xuanhe Zhou, Xu Han, Yudon… · 📄 PDF
Multi-Modal, Multi-Environment Machine Teaching for Robust Reward Learning
As autonomous agents are increasingly deployed across diverse operational contexts, aligning their behavior with human intent demands reward functions that remain robust to such changes rather than overfitting to any single environment. Inverse reinforcement learning (IRL) provides a principled way …
Ali Larian, Qian Lin, Chang Zong Wu, Daniel S. Brown · 📄 PDF
Formal Mechanisms for Market Stability in Self-Interested Agent Societies: A Marketplace Simulation Study
Self-interested agents, left unconstrained, tend toward defection in repeated social dilemmas, causing cooperative gains from trade to collapse. This paper investigates what formal mechanisms, layered on top of unrestricted communication, are sufficient for a society of such agents to maintain marke…
Eugene Ng Yi Sheng, Bingquan Shen · 📄 PDF
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-wide search and research-oriented tasks. A single ReAct-style agent is constrained by one long trajectory and limited context, making it difficult to …
Xiaoshuai Song, Liancheng Zhang, Kangzhi Zhao, Yutao Zhu, Zhongyuan Wang, Guanting Dong, Jinghan Yang, Han Li, Kun Gai, … · 📄 PDF
SolarChain-Eval: A Physics-Constrained Benchmark for Trustworthy Economic Agents in Decentralized Energy Markets
As agentic AI systems are increasingly applied to cyber-physical environments, their evaluation requires assessment of both task performance and trustworthiness. In decentralized energy markets, autonomous agents may improve market utility, but may also exploit invalid physical data, create artifici…
Shilin Ou, Yifan Xu, Luyao Zhang · 📄 PDF
A Practical Investigation of Training-free Relaxed Speculative Decoding
Speculative decoding accelerates sampling from an autoregressive LLM by using a faster auxiliary model to draft tokens which are then verified in parallel by the LLM. Standard speculative decoding is lossless: its rejection and resampling steps exactly preserve the LLM's sampling distribution. Recen…
Guoxuan Xia, Luka Ribar, Paul Balanca · 📄 PDF
ProjAgent: Procedural Similarity Retrieval for Repository-Level Code Generation
Repository-level code generation requires implementing target functions while accounting for complex cross-file dependencies and project-specific conventions. Existing retrieval methods predominantly rely on lexical, structural, or semantic similarity, often overlooking repository functions that imp…
QiHong Chen, Aaron Imani, Iftekhar Ahmed · 📄 PDF
Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents
In long-horizon tasks, decision-relevant state is often scattered across an expanding trajectory, while the action agent must surface it and act. As trajectories grow, task requirements, environment facts, prior attempts, diagnoses, and open subgoals can be buried in the context window or pushed bey…
Yifan Wu, Lizhu Zhang, Yuhang Zhou, Mingyi Wang, Bo Peng, Serena Li, Xiangjun Fan, Zhuokai Zhao · 📄 PDF
Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction
Recent progress in 3D human pose estimation has made markerless recovery of skeletal motion increasingly accurate and scalable. However, most pose estimators remain optimized for geometric keypoint accuracy, while many real-world applications in rehabilitation, sports science, ergonomics, and clinic…
Ayda Eghbalian, Kevin Desai · 📄 PDF
Validity of LLMs as data annotators: AMALIA on authority
A national language model offers a linguistic community its own instrument for measuring what its citizens say and value. Portugal's AMALIA, a publicly funded 9B-parameter model for European Portuguese, appears competitive on agreement alone: asked to code the moral foundation of authority, it agree…
Manuel Pita · 📄 PDF
The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs
Post-training quantization is widely used to deploy large language models in resource-constrained settings, yet its evaluation relies almost exclusively on accuracy and perplexity. We show that these metrics fail to capture behavioral changes induced by quantization. We introduce correctness agreeme…
Baha Rababah, Cuneyt Gurcan Akcora, Carson K. Leung · 📄 PDF
Workflow as Knowledge: Semantic Persistence for LLM-Mediated Workflows
Large language model (LLM) applications increasingly use explicit workflows for tool use, retrieval, branching, checkpointing, and human approval. Existing workflow systems already address many execution concerns. This paper proposes a Lisp-inspired but language-independent conceptual model: symboli…
Emanuele Quinto, Carlo Andrea Rozzi, Francesco Zanitti · 📄 PDF
AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding
Recent advances in Vision-Language Models, Large Language Models, and Multimodal Large Language Models have improved autonomous driving tasks such as scene understanding, decision making, trajectory prediction, and visual question answering. However, evaluating whether these models can reliably reas…
Siddharth Damodharan, Radhika Gupta, Ali Alshami, Ryan Rabinowitz, Jugal Kalita · 📄 PDF
Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph
While UMAP is widely used for exploring high-dimensional data, typical workflows focus on its lower-dimensional embedding, largely overlooking the rich k-nearest-neighbor (kNN) graph that UMAP constructs internally. This graph encodes the data manifold in its original high-dimensional space, before …
Duen Horng Chau, Donghao Ren, Fred Hohman, Dominik Moritz · 📄 PDF
Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis
In this study, we present a large-scale descriptive analysis of the use of an AI-based learning assistant (Syntea) in higher education. Based on objective log data from 77,543 students enrolled in distance studies, we examine usage patterns across gender, age group, study cluster, degree, and study …
Kristina Schaaff, Quintus Stierstorfer, Valerie Heckel · 📄 PDF
SLORR: Simple and Efficient In-Training Low-Rank Regularization
Low-rank factorization is widely used to compress neural networks, but modern models are often not naturally amenable to aggressive factorization without significant accuracy loss. Existing training-time low-rank regularizers can improve compressibility, but they often require SVDs of large weight m…
David González-Martínez, Shiwei Liu · 📄 PDF
Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biological genomes. Current benchmarks still say little about whether AI systems can follow this inheritance structure. We present IdeaGene-Bench (IG-Be…
Yifan Zhou, Qihao Yang, Yan Li, Donggang Li, Xiru Hu, Hokin Deng, Ziyang Gong, Xuanyi Zhou, Huacan Wang, Xiangchao Yan, … · 📄 PDF
OpenCoF: Learning to Reason Through Video Generation
Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video generation models offer a reasoning path distinct from previous Chain-of-Thought (CoT): reasoning can unfold through temporally connected frames, known…
Xinyan Chen, Ziyu Guo, Renrui Zhang, Dongzhi Jiang, Hongsheng Li · 📄 PDF
Cascading Effects of the COVID-19 Pandemic on Barangays in the Philippines
The COVID-19 pandemic disrupted socio-economic and healthcare systems in the Philippines, significantly affecting barangays. This study analyzes the cascading effects of the COVID-19 pandemic on key aspects of a barangay, namely mobility, accessibility of public services, economic and financial heal…
Naomi Ashley Amparo, John Frederick Muji, Paul James Montecillo, Jaymar Soriano, Vena Pearl Bongolan · 📄 PDF
Helping Hands, Healthier Infants: The Effect of Medicaid Doula Coverage Mandates on Birth Outcomes
Over the last decade a wave of U.S. states began reimbursing doula services through Medicaid, hoping to improve infant health and narrow stark racial gaps in birth outcomes. I evaluate these mandates using the staggered 2021-2024 rollout, a panel of 32.1 million births from CDC WONDER (2016-2024), a…
Farhad V. Farahani · 📄 PDF
The Impact of Publicly Funded Small Business Advisory Services: Firm Take-up and Performance in the United States
This paper studies the impact of geographic proximity to and utilization of publicly funded advisory services offered to US small businesses on firm take-up and performance. We leverage a novel administrative dataset from the Northern California Small Business Development Center (SBDC) Network cover…
Scott Kaplan, Ryan Raimondi · 📄 PDF
Inflation as an emergent phenomenon
We develop an agent-based model in which inflation emerges from decentralized price-setting and credit-financed production in an endogenous-money economy. Firms operate under working-capital constraints, form market-based price expectations through heterogeneous adaptive learning, and set prices via…
Alessio Emanuele Biondo, Mauro Gallegati · 📄 PDF
Quantum Dot Moiré from Crossed MoS2 Nanoribbons
Twisted atomically thin layers have attracted much attention for Moiré potential and correlated quantum phenomena. However, existing Moiré superlattices have largely been limited to extensive wavefunction without lateral confinement. Here we introduce a new platform where 1D nanoribbons of 2D MoS2 g…
Xinting Shuai, Hao Zhang, Wenjing Wu, Chongning Wu, Maryam Amiri, T. A. M. Ragib Shahriar, Dian Pan, Zhi Kai Ng, Tymofii… · 📄 PDF
Probing individual phonon-polaritonic nanoparticle-on-mirror cavities by infrared nanospectroscopy
Nanoparticle-on-mirror (NPoM) cavities enable extreme light confinement and strong light-matter interactions, but their realization with phonon-polariton materials in the mid-infrared spectral range remains largely unexplored. Here, we use nano-FTIR spectroscopy to study the near-field response of i…
Isabel Pascual Robledo, Iker Herrero León, Karol Kołataj, Guillermo P. Acuna, Javier Aizpurua, Philippe Roelli, Rainer H… · 📄 PDF
Ultra-high-speed chemiluminescence tomography of spinning-mode detonation waves
This work presents a chemiluminescence tomography campaign to reconstruct time-resolved, three-dimensional reacting structures in detonation waves propagating through ethylene-based mixtures at 1 atm. Images of chemiluminescence are recorded simultaneously by five cameras through a cylindrical sapph…
Amit K. Singh, Mateo Gomez, Kevin Y. Cho, Aaron W. Skiba, Samuel J. Grauer · 📄 PDF
Projected Energy Matching for Generative 3D Priors
Energy Matching has emerged as a powerful generative framework that combines flow model efficiency with the explicit likelihood of Energy-Based Models (EBMs) via a single, time-independent scalar potential. However, directly training this potential on high-dimensional 3D data remains computationally…
Daniel Barco, Michal Balcerak, Suprosanna Shit, Chinmay Prabhakar, Philipp Denzel, Bjoern Menze, Frank-Peter Schilling · 📄 PDF
A Sparse and Truncated State Vector Simulator for Peaked Circuits
In a class of quantum circuits known as peaked circuits, the goal is to predict the most probable bit string at the output of the circuit. Since these circuits are designed to have a sharp peak in their output distribution, in principle it should be possible to simulate them using a truncated state …
Diogo R. Ferreira · 📄 PDF
Identifying the MPC-Liquidity Gradient in High-Quality Data
We estimate the gradient of the Marginal Propensity to Consume (MPC) with respect to liquidity using a new estimator designed for administrative data with negligible measurement error in income. We derive a state-dependent consumption pass-through equation from the canonical buffer-stock model, and …
Mikael Carlsson, Marco D'Amico, Erik Öberg, Oskar N. Skans, Karl Walentin · 📄 PDF
Thermodynamic description of worldwide distribution of energy and carbon emission
Based on public data, we analyze the distributions of energy and carbon emission over world countries on a scale of the last 40-50 years using their presentation via Lorenz and Pareto curves. These curves in rescaled format remain remarkably stable on this time period being characterized by high val…
Klaus M. Frahm, Dima L. Shepelyansky · 📄 PDF
The Joneses Visit an Economics Lab
Existing literature offers persuasive evidence that individuals care about how their consumption compares to that of peers, and proposes a large variety of explanatory models. The present paper proposes a common framework for many of those models, and compares their ability to predict behavior in a …
Mikhail Freer, Daniel Friedman, Christian Ghiglino, Elke Weidenholzer · 📄 PDF
Answering Without Referring: How AI Search Rewrites the Web's Economic Bargain
Search engines have long allocated attention on the web by routing users from queries to websites. AI search changes this arrangement because information needs can be resolved inside the intermediary. Using URL-level Comscore U.S. desktop clickstream, we compare ChatGPT and Google information-seekin…
Qiaoni Shi, Kai Zhu, Kai Gu · 📄 PDF
Robustness to Model Uncertainties Drives More Rapid CO2 Emissions Reductions
Evaluating the economic impacts of climate policies is important for designing a response to climate change. One typical approach to assessing mitigation policy options uses integrated climate-economy models to analyze tradeoffs between the costs of reducing greenhouse gas emissions and the benefits…
Lisa Rennels, Frank Errickson, David Smith, Bryan Parthum, Klaus Keller, David Anthoff · 📄 PDF
Beyond Silica Assumptions: Optical Network Design in the Hollow-Core Era
Hollow-core fiber (HCF) is often presented as a modestly improved transmission medium that can be inserted into networks originally designed for solid-core silica. We argue instead that recent progress -- most notably the reported attenuation below 0.1 dBkm$^{-1}$, together with a broad low-loss win…
Md Ghulam Saber, Zhiping Jiang · 📄 PDF
Exoplanet Detection Using Adaptive Quantum-Optimal Measurement
Detecting terrestrial exoplanets in the habitable zones of nearby stars remains a critical challenge. Such planets can be \(10^8\) to \(10^{10}\) times fainter than their host stars and lie at diffraction-limited angular separations, where starlight strongly obscures the companion signal. Here we pr…
Hyunsoo Choi, Hyoung Won Baac, Zubin Jacob, Haejun Chung · 📄 PDF
Single-laser stimulated Brillouin scattering microscopy
Stimulated Brillouin scattering (SBS) microscopy enables label-free mapping of local viscoelastic properties, but frequency-domain implementations are often limited by uncertainty in the pump-probe frequency-difference axis. We demonstrate an RF-defined single-laser electro-optic-modulation SBS micr…
Feihong Lin, Zechao Wen, Jiahui Li, Xiaoyu Yang, Haonan Zhang, Jiahe Zhang, Peiqing Zhang, Xu Liu, Qing Yang · 📄 PDF
Terahertz Generation through Photon Deceleration of Long-Wavelength Infrared Laser Pulses in Plasma
Efficient terahertz (THz) generation with high field amplitude and pulse energy is studied through the interaction of a single-color long-wavelength infrared (LWIR) laser pulse with gaseous targets. Particle-In-Cell (PIC) simulations are performed to investigate the underlying mechanism and analyze …
Srimanta Maity · 📄 PDF
Scalar-Wave Dispersion in Vectorial Photonic Crystals via Site-Adapted p Orbitals
Electromagnetic waves are intrinsically vectorial and require description via polarization, unlike scalar fields such as acoustic pressure or electronic wavefunctions. In three dimensions, the transversality constraint further prevents any globally smooth transverse-polarization frame at the $Γ$ poi…
Yan-Long Chen, Kin Hung Fung, C. T. Chan, Qinghua Guo · 📄 PDF
Rayleigh Bound States in the Continuum
We predict a class of bound states in the continuum (BICs) in non-subwavelength periodic metasurfaces -- Rayleigh BICs -- that emerge precisely at Rayleigh anomalies, where diffraction channels open. In contrast to conventional symmetry-protected and accidental BICs, which are typically engineered i…
Ilya Karavaev, Mingzhao Song, Andrey Bogdanov · 📄 PDF
Beyond white- and black-box modeling tools in optical communications and optical computing: physics-informed data-driven modeling
Efficient optimization and control of photonic computing and communication systems increasingly rely on accurate surrogate models/digital twins. While data-driven models may achieve faster inference than traditional physics-based methods, they typically suffer from poor training data efficiency and …
Isidora Teofilovic, Sergio Hernandez Fernandez, Metodi P. Yankov, Christophe Peucheret, Darko Zibar, Francesco Da Ros · 📄 PDF
Pulley coupler engineering for frequency comb generation based on the supermodal approach
Light coupling into integrated microresonators is typically achieved using straight bus couplers that are optimized to achieve critical coupling at the pump wavelength but lack spectral engineering capabilities. Pulley couplers offer additional degrees of freedom and opportunities, but optimizing th…
Lise Morice, Baptiste Routier, Quentin Wilmart, Christian Grillet, Christelle Monat, Yoan Léger · 📄 PDF
Time domain Stokes mechanism of pair correlated k gap solitons in nonlinear photonic time crystal slabs
Pair generation in time-varying media is commonly attributed to time reflection at temporal boundaries or to amplification inside momentum k gaps. Here we show that these two processes are connected by the time domain Stokes phenomenon. A finite duration photonic time crystal (PTC) slab provides the…
Jiaxiang Sun, Guowei Chen, Liang Zhang, Yiming Pan · 📄 PDF
Transmissibility, boundary-guided waves, and representative unit cell choice in finite-sized metamaterials
The implications of selecting different unit cells are often overlooked in both direct studies of microstructured materials and their homogenized equivalents. Investigating the effects of unit cell selection is crucial not only for understanding boundary phenomena but also for identifying which fini…
Plastiras Demetriou, Gianluca Rizzi · 📄 PDF
Coexistence and manipulation of multiple singularities in a reconfigurable non-Hermitian metasurface
Non-Hermitian frameworks extend conventional Hermitian physics, offering a powerful paradigm for describing open systems. Central to this field are various singularities within the complex parameter space, such as exceptional points (EPs) and scattering zeros, which dictate exotic physical behaviors…
Xintong Shi, Yanjie Wu, Rui Zhou, Zuxing Lu, Tengyu Li, Tingting Liu, Hai Lin, Qiegen Liu, Shuyuan Xiao · 📄 PDF
Chip-scale nanostructured chaotic billiards for broadband speckle spectrometry
Computational on-chip spectrometers are emerging as a powerful platform for portable spectral analysis, combining photonic integration with advanced signal processing to enable a wide range of in-situ sensing applications. We propose a broadband reconstructive spectrometer based on wave chaos in a s…
Matthew R. Wilson, Benoit Guilhabert, Jack A. Smith, Michael J. Strain, Xavier Porte · 📄 PDF
Spin Textures and Eigenstate Evolution of Isospectrally Patterned Lattices
Isospectrally patterned lattices exhibit a composite band structure with a tunable ratio of localized versus delocalized eigenstates that is controlled by the underlying phase gradient. We show that the lattice Hamiltonian can be interpreted as that of a single spin exposed to a rotating magnetic fi…
Peter Schmelcher · 📄 PDF
Analysis of polarization drift of optical signals over deployed aerial-inground fiber connections
Polarization measurements of a classical 1550-nm signal are collected and analyzed on 15-km hybrid aerial-inground fiber connections over 11 months. The spectral area and spectral moments9 of mHz-resolution Fast-Fourier-Transform (FFT) of these measurements are extracted, and related to temperature,…
Aneesh Ramaswamy, Nageswara S. V. Rao, Joseph C. Chapman, Muneer Alshowkan · 📄 PDF
Distributed Circuit Model for Predicting the Quality Factor of Magnetic Polariton Resonance
Existing RLC circuit model leads to inaccurate predictions of the quality factor (Q-factor) of magnetic polariton (MP) resonances under imperfect absorption conditions due to the omission of radiation loss. Moreover, the lumped-parameter nature of RLC models also limits their applicability for predi…
Hangjie Li, Junming Zhao · 📄 PDF
Pic2Spec: Generative Modeling Reconstructs Single Cell Raman Fingerprints from Brightfield Images
Single-cell molecular characterization remains a bottleneck in scalable biological analysis because of labeling requirements, limited multiplexing, and reagents that perturb physiology. Raman spectroscopy addresses these limits by providing chemically specific, label-free vibrational fingerprints, b…
Srilakshmi Premachandran, Amit Kumar Bhuyan, Loza F. Tadesse · 📄 PDF
Predicting Multi-Order Magnetic Polariton Resonances for Radiative Properties Tailoring by Distributed Circuit Model
Surface plasmon polaritons (SPPs) and magnetic polaritons (MPs) are fundamental resonance modes that are widely used to tailor the thermal radiation properties of micro/nanostructured metamaterials. Lumped circuit models (LCMs) are usually constructed empirically to describe the MP resonance conditi…
Hangjie Li, Junming Zhao · 📄 PDF
Reliable mechanistic operator recovery with biologically-informed neural networks: principles for architecture and optimisation design
Many biological processes are governed by complex dynamical mechanisms that remain incompletely understood despite increasing volumes of experimental data. Biologically-informed neural networks (BINNs) seek to address this challenge by embedding mechanistic differential equations into neural network…
Rebecca M. Crossley, Yuan Yin, Sarah L. Waters, Ruth E. Baker · 📄 PDF
Collaborate to decorrelate in path space: Hamiltonian replica exchange transition interface sampling (HRETIS)
We present Hamiltonian Replica Exchange Transition Interface Sampling (HRETIS), a path sampling framework designed to efficiently sample rare events in systems with complex potential energy landscapes. HRETIS introduces a helper potential within a Hamiltonian replica exchange scheme, which enhances …
Sina Safaei, Parham Rezaee, An Ghysels · 📄 PDF
Equivalence testing in pesticide risk assessment -- Evaluation and practical guidance for design, analysis and interpretation
Harmful pesticide effects exceeding specific protection goals (SPG) may go undetected in underpowered experimental designs. Regulatory honeybee field studies have consistently failed to reach the statistical power required under European Food Safety Authority (EFSA) guidance, which may have caused a…
Dimitry Wintermantel, Julia Osterman, Magdalena M. Mair, Florian Hartig · 📄 PDF
A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling
Large language models (LLMs) demonstrate remarkable reasoning capabilities, yet their stateless architecture fundamentally limits deployment in long-horizon research workflows requiring multi-session continuity and quantitative rigor. Here we present Ensemble QSP, a multi-agent framework featuring a…
Shivendra G. Tewari, Holly Kimko · 📄 PDF
Rethinking the Choice Behavior of Sugar Metabolism in Bacteria
Ramkrishna, Kompala, and Tsao proposed the cybernetic model of microbial growth, in which cells allocate enzyme synthesis resources according to a matching rule that mimics rational decision-making. The matching rule was later shown to be optimal under general assumptions about the underlying return…
Jeffrey D. Varner · 📄 PDF
A quantum model for synchronizing finite state transition systems
We propose a quantum model for finding a resetting input sequence (RS) which can take a finite state transition system (FA), to particular state independent of its current state. The complexity of finding such sequences for various types of FA can be NP-Hard or even PSPACE-Complete. To this end, we …
Martin Lukac, Khaled El-Fakih, Uraz Turker · 📄 PDF
Quantum Sampling Architecture for Protein Structure Reconstruction on Utility-Scale Hardware
Predicting the structure of short peptides in protein binding pockets remains difficult because this regime requires physics-based conformational search, yet existing methods do not provide a practical way to carry out that search on current hardware. We present QSAD, a quantum-classical framework t…
Yuqi Zhang, Bo Fang, Yuxin Yang, Feixiong Cheng, Jieyang Chen, Sherry Fang, Siwei Chen, Junhan Zhao, Qiang Guan · 📄 PDF
Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production
AI agents deployed for IT operations are typically permanent cost centers because every execution requires full LLM inference, even for previously solved problems. This paper introduces progressive crystallization, a lifecycle that treats agent exploration as a discovery mechanism rather than a perm…
Arun Malik · 📄 PDF
Deanonymizing Monero Transactions in Tor Network
Monero is a privacy-focused cryptocurrency that deploys the Dandelion++ protocol and incorporates anonymity networks (such as Tor and I2P) to prevent malicious attackers from linking transactions with their source IPs. In this paper, we demonstrate that Monero's integration of the Tor network introd…
Ruisheng Shi, Shihan Zhang, Yulian Ge, Lina Lan, Qingfeng Zhang, Qin Wang · 📄 PDF
Analytical Landscape of Maximal Magic for Two-Qutrit States and Beyond
Achieving a genuine quantum advantage relies on two distinct non-classical resources that restrict efficient classical simulation: entanglement and magic (nonstabilizerness). We investigate the interplay between these resources by characterizing the Pareto frontiers of extreme magic at fixed entangl…
Marco Knipfer, Alexander Roman, Katia Matcheva, Konstantin T. Matchev · 📄 PDF
-8 dB SNR + 90% Packet Loss: MamVSC -- CSI-Guided Semantic Mamba for Extreme-Robust Video Semantic Communication
Semantic communication, leveraging joint source-channel coding, is designed to mitigate semantic distortion introduced by the channel. However, most current studies focus solely on semantic deviation distortion caused by physical wireless channels, while overlooking semantic erasure distortion due t…
Lei Teng, Senran Fan, Chen Dong, Haotai Liang, Xiaodong Xu, Ping Zhang · 📄 PDF
Resource-Efficient Hybrid Quantum Neighborhood Selection for Large-Scale Molecular Diversity Optimization
Large-scale combinatorial optimization remains demanding for classical heuristics, particularly when dense Quadratic Unconstrained Binary Optimization (QUBO) formulations induce large memory footprints, high CPU utilization, and long execution times. While near-term quantum processors cannot yet del…
Nicolas Mendes de Araujo, Lester de Abreu Faria · 📄 PDF
LLM Assisted Verification Assertion Generation: Challenges and Future Directions
Assertion-based Verification (ABV) plays a critical role in the Design Verification (DV) process. However, ABV requires substantial manual effort in generating assertion from specification by verification engineers, making it a time-consuming stage in the chip design flow. With the recent developmen…
Bhabesh Mali, Chandan Karfa · 📄 PDF
Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising for edge AI. However, as an image usually contains much spatial redundancy, e.g., background pixels, directly shrinking the whole image will lose impo…
Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin · 📄 PDF
EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI
Convolutional neural networks (CNNs) have demonstrated encouraging results in image classification tasks. However, the prohibitive computational cost of CNNs hinders the deployment of CNNs onto resource-constrained embedded devices. To address this issue, we propose EdgeCompress, a comprehensive com…
Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu · 📄 PDF
ThermoDSE: A Thermal-Aware and Comprehensive Design Space Exploration for Chiplet-Based DNN Accelerators
Chiplet-based DNN accelerators provide a scalable path to balance performance and yield for modern AI workloads. However, such systems face critical challenges in area and thermal constraints. Design space optimization should jointly consider fine-grained task modeling, chiplet granularity, core gra…
Jian Peng, Hanwei Fan, Jingbo Jiang, Lin Jiang, Wei Zhang · 📄 PDF
Miter-Aware LUT Mapping: Aligning Structure and Solvability for Efficient Logic Equivalence Checking
Logic Equivalence Checking (LEC), a fundamental hardware verification task, is often bottlenecked by synthesis-induced structural perturbations and XOR-dense regions that degrade SAT solver performance. We contend that the modeling of the miter is as critical as the SAT solver itself. To this end, w…
Jiaying Zhu, Zhengyuan Shi, Mengxia Tao, Kezhi Li, Min Li, Qiang Xu · 📄 PDF
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency
We analyze how four forces restructure the AI industry over 2026-2030: the DRAM/HBM price surge, frontier-capable open-weight models (GLM-5.2), rapid inference-efficiency gains (near-Shannon-limit KV-cache compression, lightweight local runtimes), and the entry of Meta and xAI into compute resale on…
Satoshi Matsuoka · 📄 PDF
Vectorizing Quantum Control: A RISC-V Vector Extension Architecture for Scalable Qubit Systems
The Quantum Control Processor (QCP) bridges the gap between compiler toolchains and control electronics, and is responsible for translating compiled quantum circuits into executable instructions that directly manipulate qubits and handle measurement feedback. However, existing designs rely primarily…
Xiaorang Guo, Kun Qin, Yanbin Chen, Carsten Trinitis, Martin Schulz · 📄 PDF
Embedded Blockchain Infrastructure Management (eBIM): A RISC-V-Empowered Hardware--Software Co-Design Framework Towards Trustworthy Blockchain
Blockchain systems are undergoing a fundamental transition from decentralized ledgers for digital assets to general-purpose trust infrastructures for verifiable computation, decentralized physical resources, and automated infrastructure management. Meanwhile, the limitations of the Blockchain as a S…
Qinglin Yang, Yuan Liu, Yaoyao Zhang, Boya Wang, Zongjian You, Chunming Rong, Zhihong Tian · 📄 PDF
ATLAS: Automated HLS for DL-Optimized FPGAs
FPGA architectures increasingly incorporate domain-specific in-fabric hardblocks to accelerate DL inference, particularly GEMM, which dominates DL computation. To realize the performance gains of these hardblocks, manual RTL design is required: the programmer must understand the hardblock microarchi…
Ruthwik Reddy Sunketa, Aman Arora · 📄 PDF
Programmable Synchronization Graphs for Adaptive and Fault-Tolerant Modular Miniature Robots
Modular miniature robots could provide scalable function in constrained environments, but coordinating many imperfect modules remains difficult when computation, communication and reliability are limited. A central robotics challenge is to coordinate many actuator-sensor modules without assigning a …
Okan Kulekcioglu, Arqam Bin Ahmad, Ines Garcia, Filipe Serra Alves, Onur Ozcan, M. Selim Hanay · 📄 PDF
TouchWorld: A Predictive and Reactive Tactile Foundation Model for Dexterous Manipulation
Dexterous manipulation in everyday environments requires both anticipation and reaction: a robot must predict how contact should evolve while rapidly correcting local errors caused by slip, misalignment, unstable grasping, or force mismatch. Vision and language provide semantic and geometric guidanc…
Jianyi Zhou, Feiyang Hong, Yunhao Li, Yicheng Zhao, Yongjue Cen, Zirui Liu, Jiakang Huang, Zirui Chen, Ruiyang Zhang, We… · 📄 PDF
Multimodal Voice Activity Projection for Turn-Taking in Social Robots with Voice-Activity-Related Pretrained Encoders
Turn-taking prediction is a key requirement for social robots involved in human-human interaction, particularly in mediator settings, where the robot must anticipate conversational dynamics rather than merely react to pauses. This work presents a Multimodal Voice Activity Projection (MM-VAP) framewo…
Antonio Cano, Guillermo Pérez, Luis Merino, Randy Gomez · 📄 PDF
HumAIN: Human-Aware Implicit Social Robot Navigation
Effective social robot navigation requires sensitivity to human behavior, often revealed through subtle skeletal cues like gait and orientation. We present Human-Aware Implicit Social Robot Navigation (HumAIN), a novel framework that fuses implicit social cues directly into the planning loop via kno…
Daeun Song, Nhat Le, Jeffrey Chen, Mohammad Nazeri, Amirreza Payandeh, Rohan Chandra, Reuth Mirsky, Ross Mead, Ling Xiao… · 📄 PDF
Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report
In embodied intelligence systems, the motion controller serves as the critical bridge between semantic reasoning and physical execution. Humanoid control has progressed rapidly through large-scale human motion-capture data and motion-tracking paradigm. However, producing quadruped robots motion corp…
Xufeng Zhao, Fuzhi Yang, Jianhui Chen, Li Gao, Zhang Meng, Jie Gao, Yao Zheng, Wenyu Liu, Menglin Yang, Minqi Gu, Yaru Z… · 📄 PDF
PLED-VINS: A Point-Line Event-Based Visual Inertial SLAM for Dynamic Environments
Dynamic environments remain a fundamental challenge for visual SLAM, where unreliable observations from moving objects and rapid motion degrade state estimation accuracy. Although event cameras preserve fine-grained spatio-temporal information, most existing event-based SLAM frameworks still assume …
Seunghun Lee, Jihun Nam, Dong-Uk Seo, Hyun Myung · 📄 PDF
Communicative Efficiency of Single vs. Multi-Axis Robot Neck Motion
Nonverbal communication through head and neck movement is fundamental to human social signalling, yet how robotic neck morphology translates motion into communicative information remains poorly understood. We present an information-theoretic framework characterising robot neck movement as a communic…
Chapa Sirithunge, Haewon Jeong, Qinghua Guan, Fumiya Iida, Josie Hughes · 📄 PDF
Multi-Agent Robotic Control with Onboard Vision-Language Models
Vision Language Models (VLMs) and Vision Language Action (VLA) models have shown promise in robotic control. Yet, they face significant challenges regarding explainability, generalization, and compute requirements. This paper presents a Multi-Agent System (MAS) architecture that addresses these limi…
Kajetan Rachwał, Maciej Majek, Bartłomiej Boczek, Jakub Matejczyk, Dominik Matejkowski, Adam Dąbrowski, Tim Seyde, Alexa… · 📄 PDF
Initiation Safety: A Missing Dimension in Generalist-Robot Safety
Safety for generalist robots is usually discussed in terms of motion or dialogue. We argue a third question is missing: should the robot take its first hard-to-undo social action at all, such as a greeting, an uninvited grasp, or stepping into someone's space? We call this initiation authorization. …
Zhijin Meng, Francisco Cruz · 📄 PDF
Immersive Social Interaction with VR and LLM-Assisted Humanoids
Humanoid robots can extend human presence to remote, constrained, or hazardous environments, but existing teleoperation interfaces often require physically demanding motion tracking or cognitively demanding low-level control. This paper presents an immersive teleoperation framework that integrates v…
Niraj Pudasaini, Geeta Chandra Raju Bethala, Pranav Doma, Anthony Tzes, Yi Fang · 📄 PDF
GeoGS-SLAM: Geometry-Only Gaussian Splatting for Dense Monocular SLAM
Dense visual SLAM is a fundamental problem in robotics. Recent advances in 3DGS have demonstrated its potential for dense SLAM. Existing 3DGS frameworks focus on both appearance and geometry modeling. However, scene geometry is typically more critical for SLAM than novel view synthesis because downs…
Lipu Zhou, Yaoyun Kang, Junxiang Pang, Shengkai Sun, Tingting Bao, Kehan Wang · 📄 PDF
Agent-Exploitation Affordances: From Basic to Complex Representation Patterns
In robotics, the capability of an artificial agent to represent the range of its action possibilities, i.e. affordances, is crucial to understand how it can act on its environment. While functional affordances, which refer to the use of tools and objects, have been broadly studied in knowledge repre…
Bastien Dussard, Aurélie Clodic, Guillaume Sarthou · 📄 PDF
Smooth Operator: A Real-Time Sampling-Based Algorithm for Kinematic Hand Retargeting
Advances in learning-based robotic manipulation, such as Vision-Language-Action (VLA) models and Video Action Models (VAMs), heavily rely on high-quality teleoperation data. Their capabilities are strictly upper-bounded by the quality of the underlying human demonstrations. Current gradient-based re…
Robert Jomar Malate, Erik Bauer, Norica Bacuieti, Stefanos Charalambous, Elvis Nava, Robert K. Katzschmann, Benedek Forr… · 📄 PDF
Generating Personalized Lower-Limb Kinematics Across Walking Speeds Using Subject-Conditioned Diffusion
Personalizing exoskeleton assistance requires user-specific gait data across many locomotor tasks, yet collecting this data demands repeated motion capture sessions that are costly, time-intensive, and especially burdensome for clinical populations. This challenge is most acute across walking speeds…
Diya Dinesh, Adrian Krieger, Changseob Song, Dongho Park, Aaron J. Young, Inseung Kang · 📄 PDF
Context-Aware Force Estimation for Deformable Tool Manipulation in Robotic Environmental Swabbing via Few-Shot Continual Adaptation
Robotic surface swabbing requires sustained interaction between a compliant tool and heterogeneous environments, where accurate estimation of tip-level contact force is critical for consistent sampling performance. However, deformable tool dynamics introduce nonlinear viscoelastic hysteresis that de…
Siavash Mahmoudi, Chaitainya Kuppar Reddy, Yang Tian, Dongyi Wang · 📄 PDF
Continuous and large-scale: ELEANOR, the soft architected arm inspired by the elephant trunk
The elephant trunk is a dexterous and versatile manipulator whose performance is still unmatched in robotics. In previous works, modularity was prioritized and relatively small-scale continuum robots were built. We take the natural proboscis of the *Loxodonta africana* species as a model and propose…
Giovanna A. Naselli, Anderson B. Nardin, Seonggun Joe, Ryan Drinkwater, Enrico Donato, Diego Bianchi, Egidio Falotico, M… · 📄 PDF
When Prompts Ignore Structure: Graph-Based Attribute Reasoning for Calibrated VLMs
Reliable confidence estimation remains a key limitation of test-time adaptation in vision-language models (VLMs), where prompt tuning improves zero-shot accuracy but often degrades calibration due to entropy-driven overconfidence. Prior approaches mitigate this using LLM-derived class attributes and…
Tanay Sodha, Aditya Sharma, Ramya Hebbalaguppe, Vinti Agarwal, Pranav Murthy Yeluripaty · 📄 PDF
Heterogeneity-Adaptive Diffusion Schrodinger Bridge for PET-Guided Whole-Body MRI Translation
While whole-body multimodal medical imaging scanners have been increasingly recognized for more effective medical applications, the excessive long acquisition time in PET-MR scanning is a major obstacle in more efficient clinical practice. Deep learning-based MRI translation provides a potential sol…
Chengbo Wang, Jiacheng Yu, Linjie Bian, Ming Qi, Xiaosheng Liu, Tongtong Che, Jichang Zhang, Shuyu Li, Shaoli Song, Xiuy… · 📄 PDF
VCDP: Variation-Conditioned Distributional Proxy Learning for Semi-Supervised Medical Image Segmentation
Semi-supervised 3D medical image segmentation reduces the need for dense voxel-level annotations by exploiting unlabeled volumes. Although existing methods such as consistency regularization, pseudo-labeling, and co-training improve prediction-level robustness, they often provide insufficient featur…
Zimu Zhang, Yiheng Zhong, Zhuoru Zhang, Yingzhen Hu, Yanan He, Fanliang Meng, Xiaofeng Liu · 📄 PDF
Two-Stage Multi-Modal Fusion with Adaptive Alignment for Action Quality Assessment
Action Quality Assessment (AQA) aims to evaluate how well a person performs a movement, which is essential in applications such as sports scoring, skill assessment, and healthcare. However, unimodal approaches often struggle to capture subtle cues of movement quality in real-world settings. Although…
Kanglei Zhou, Ruizhi Cai, Xinning Wang, Yijian Zheng, Liyuan Wang, Jianguo Li, Xiaohui Liang · 📄 PDF
EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI
We present EmbodiedGen V2, a generative 3D world engine for building executable sim-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapidly, yet assembling such assets into policy-ready task environments remains largely manual, limiting scalable closed-loop l…
Xinjie Wang, Liu Liu, Taojun Ding, Andrew Choi, Chaodong Huang, Mengao Zhao, Ziang Li, Jackson Jiang, Chunlei Yu, Shengx… · 📄 PDF
A Theory of Contrastive Learning with Natural Images
Why does contrastive learning with simple images and augmentations yield useful representations for downstream tasks? We address this question by analytically computing the optimal representation in terms of a contrastive loss for a range of basic augmentations and any image dataset with stationary …
Antonio Torralba, Yair Weiss · 📄 PDF
Discovering Geometric Biases in 3D Face Reconstruction: A Curvature-Aware Spectral Framework for Fairness Evaluation
3D Morphable Models (3DMMs) remain the standard parametric shape priors for many state-of-the-art 3D face reconstruction algorithms. However, as these models are derived from a finite number of 3D face samples, they inherit the morphological biases of their training data, potentially limiting their …
Veronika Shilova, Emmanuel Malherbe, Giovanni Palma, Panagiotis-Alexandros Bokaris, Laurent Risser, Jean-Michel Loubes · 📄 PDF
Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification
Deformable shape representations have proven to be robust complements to texture features in cardiac image classification, offering geometric priors that are invariant to imaging artifacts and intensity variations. However, existing deep networks perform simple concatenation to combine these distinc…
Tonmoy Hossain, Miaomiao Zhang · 📄 PDF
Context-Aware Slum Mapping in Sub-Saharan Africa Using Sentinel-1 Texture and Local Climate Zones
Accurate mapping of informal settlements remains a major challenge in Sub-Saharan African (SSA) cities because optical imagery often fails to distinguish Informal Settlements (defined here as LCZ 7) from spectrally similar formal Compact Low-Rise areas (LCZ 3). This study presents a context-aware, r…
Peterson Chepkilot, Babak Memar, Paolo Gamba · 📄 PDF
Infinite Worlds with Versatile Interactions
We present LingBot-World 2.0 (also known as LingBot-World-Infinity), an advanced iteration of LingBot-World featuring four distinct upgrades. (1) Our model achieves an unbounded interaction horizon while maintaining consistent output quality, benefiting from a carefully crafted causal pretraining pa…
Zelin Gao, Qiuyu Wang, Jiapeng Zhu, Jingye Chen, Zichen Liu, Qingyan Bai, Jiahao Wang, Yufeng Yuan, Hanlin Wang, Yichong… · 📄 PDF
SonoRank: Towards Calibration-Free Real-Time Finger Flexion Detection from Forearm Ultrasound Sequences
Powered prosthetic hands are frequently abandoned, largely due to the limited functionality of current devices that rely on surface electromyography (sEMG). Sonomyography (ultrasound) has emerged as a promising alternative, owing to its ability to observe muscle activity in real time and control a g…
Dean Zadok, Alon Wolf, Alex M. Bronstein, Oren Salzman · 📄 PDF
Face-trace: Open-Set Attribution and Progressive Discovery of Synthetic Face Generators
Recent advances in generative Artificial Intelligence have made synthetic face images increasingly realistic, creating new challenges for multimedia forensics. Source attribution methods should not only identify the generator of an image when the source is known, but also handle samples produced by …
Alessia Infantino, Claudio Schiavella, Irene Amerini · 📄 PDF
AA-ViT: Anatomically Aware Vision Transformer with Structural and Frequency Guidance for Contrast Enhanced Brain MRI Synthesis
Accurate tumour localization and diagnosis is a critical component of clinical care for brain cancers. Magnetic Resonance Imaging (MRI) is the most commonly used imaging modality due to its superior soft-tissue contrast. However, standard MRI often exhibits limited contrast and imaging artifacts, wh…
Talha Meraj, Tom Flannery, Charlie Cummins, Matt Townend, Thomas C Booth, Peter Crossley, Michael McCann, Ian Overton, S… · 📄 PDF
Automatic Echocardiography Segmentation via Transition Probability Correlation for Stable Semantic Extraction
While echocardiography is essential for cardiovascular diagnosis, inherent speckle noise and low signal-to-noise ratio often lead to ambiguous semantic features and fragmented boundaries. These limitations significantly hinder the segmentation accuracy of deep learning models in complex clinical cas…
Xinran Chen, Xiyuan Wang, Guangquan Zhou, Chuan Chen · 📄 PDF
Cardiac MRI Through-Plane Super-Resolution Guided by Reference and Memory
Clinical cardiac MRI is commonly acquired with high in-plane resolution but coarse through-plane resolution to reduce scan time and accommodate breath-hold and cardiac-motion constraints, which limits 3D analysis and diagnostic accuracy. We propose STRMSR, a reference- and memory-guided through-plan…
Shaoming Pan, Chenchuhui Hu, Leon Axel, Meng Ye · 📄 PDF
Dual Latent Memory in Vision-Language-Action Models for Robotic Manipulation
Mainstream Vision-Language-Action (VLA) models predict actions primarily from the current observation under a Markovian assumption, thus struggling with long-horizon, temporally dependent tasks. Existing memory-augmented VLAs either expand the observation window or retrieve history from the memory b…
Hongyu Qu, Jianzhe Gao, Xiaobin Hu, Shaohuan Yang, Xinlei Yu, Rui Yan, Wenguan Wang, Xiangbo Shu, Shuicheng Yan · 📄 PDF
Scaling Mixture-of-Experts Video Pretraining for Embodied Intelligence
Despite the recent promise in robot control, video generative models suffer from a domain mismatch due to their primary focus on content creation. For example, their design inherently prioritizes visual fidelity and creativity over computational efficiency and physical realism. In this work, we pres…
Shuailei Ma, Jiaqi Liao, Xinyang Wang, Jingjing Wang, Chaoran Feng, Zijing Hu, Chong Bao, Zichen Xi, Yuqi Gan, Weisen Wa… · 📄 PDF
Multi-Class vs. Multi-Label BERT for CVE-to-CWE Mapping: How Taxonomy Structure Shapes the Errors
Assigning Common Weakness Enumeration (CWE) categories to Common Vulnerabilities and Exposures (CVE) records remains an important but largely manual step in vulnerability analysis. We study this task as a text classification problem and compare two modelling choices: a \emph{multi-class} formulation…
Ana Schwengber Kelm, Christian Bockermann, Jörg Frochte · 📄 PDF
Asymmetric Focal Loss Improves Graph Neural Network Prediction of Drug-Drug Interactions
Background: Graph neural networks improve computational prediction of polypharmacy side effects, but standard binary cross-entropy training allocates equal capacity to well-classified and difficult examples, potentially missing clinically significant interactions. We evaluated whether an asymmetric …
Faranak Hatami, Mousa Moradi · 📄 PDF
Higher-Order Geometric Updates for Levenberg-Marquardt Method via Riemann Normal Coordinates
Nonlinear least-squares optimization is central to regression, physics-informed neural networks, and other machine-learning tasks. Such problems have a natural geometric interpretation, model predictions form a manifold in data space, while the chosen parameterization can introduce parameter-effects…
Jianing Liu, Dong H. Zhang · 📄 PDF
An optimal control approach for neural network architecture adaptation with a posteriori error estimation
This work presents a novel approach for adapting neural network architecture along the depth based on a posteriori error estimation. By formulating neural network training as a continuous-time optimal control problem, we derive rigorous error estimates that quantify how approximation error distribut…
C G Krishnanunni, Thomas Scott, Tan Bui-Thanh · 📄 PDF
Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance
Classifier-free guidance (CFG) is the standard way to strengthen class-conditioning in diffusion and flow-matching samplers, yet at large guidance it oversaturates and destabilizes, symptoms practitioners suppress with more steps or limited-interval schedules. We analyze CFG through an asymptotic-pr…
Shiheng Zhang · 📄 PDF
Does Bielik Know What It Doesn't Know? Activation Dispersion Separates Entity Familiarity from Factual Reliability Across Model Scale
Large language models hallucinate most about entities they have never seen. We ask whether a model's activations betray entity familiarity before a single answer token is generated, and whether that signal predicts the factual reliability of the answers. On four Polish Bielik models (1.5B-11B parame…
Grzegorz Brzezinka · 📄 PDF
PeTeR: Post-Training Robustification of Probabilistic Circuits
Probabilistic circuits (PCs) can model complex joint distributions while supporting exact and efficient computation of many inference queries. However, standard likelihood-based PC learning is vulnerable to overfitting and fragile generalization when confronted with data noise, small sample sizes, o…
Adrian Ciotinga, Yeming Dai, YooJung Choi · 📄 PDF
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by limited access to large-scale, high-quality clinical data. Although PubMed Central (PMC) offers a complementary source …
Hyunjae Kim, Dain Kim, Pan Xiao, Serina S. Applebaum, Younjoon Chung, Xuguang Ai, Yu Yin, Roy Jiang, Yuexi Du, Yawen Wei… · 📄 PDF
Max Out GRPO Signal: Adaptive Trace Prefix Control for Hard Reasoning Problems
Group Relative Policy Optimization (GRPO) stalls on a model's hardest problems: when no rollout in a group succeeds, the group-relative advantages vanish and the problem contributes no gradient, wasting the frontier examples we most want to learn from. Prepending a correct prefix of a reference solu…
Vladislav Beliaev · 📄 PDF
How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization
Rotary Position Embeddings (RoPE) provide transformers with a fixed grid of positional frequencies, yet trained models use these frequencies highly non-uniformly. We study what determines this frequency usage and propose a data-centered explanation: RoPE frequencies are selected to match the relativ…
Xinyi Wu, Siyuan Liu, Ali Jadbabaie · 📄 PDF
Any-Dimensional Learning by Sampling
Many machine learning models are defined for inputs of different sizes, such as point clouds containing different numbers of points, sequences of tokens of different lengths, and graphs on different numbers of nodes. Such models are trained on finitely-many examples of necessarily limited sizes. How…
Eitan Levin, Venkat Chandrasekaran · 📄 PDF
Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization
The inverse design of physical systems governed by partial differential equations is computationally demanding due to the high dimensionality and non-convexity of design spaces. Generative models for inverse design often lack robustness and transferability, whereas evolutionary strategies are robust…
Xiangming Huang, Guannan Zhang, Lu Lu, Raphaël Pestourie · 📄 PDF
ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening
Electrocardiography (ECG) is one of the most widely used tests for diagnosing cardiovascular disease. Yet several remote clinics still utilize paper ECG printouts for their analysis due to limited connectivity and computational capacity. As a result, vast numbers of physical ECGs obtained in remote …
Shreyasvi Natraj, Cyrus Achtari, Felice Gragnano, Andrea Milzi, Marco Valgimigli, Diego Paez-Granados · 📄 PDF
The Key to Going Linear: Analysis-Driven Transformer Linearization
The quadratic cost of causal self-attention severely bottlenecks long-context transformer inference. While numerous post hoc linearization pipelines exist, it is difficult to identify which components preserve model quality. This work isolates the effect of state update design in a strict frozen-bac…
Anna Kuzina, Paul N. Whatmough, Babak Ehteshami Bejnordi · 📄 PDF
HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models
Hallucinations in vision language models (VLMs) are commonly treated as semantic errors, yet they often arise from partial or ambiguous visual evidence. Prior work mainly focuses on detecting or suppressing hallucinations at generation time, leaving the subsequent reasoning stage largely unexplored.…
Feng He, Zhenting Wang, Qifan Wang, Qiang Guan, Dongfang Liu, Ruixiang Tang, Qiankun Li · 📄 PDF
Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning
Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs). Previous RL pipelines for LLMs were mostly synchronous and batch-interleaved, which is inefficient for long-horizon agentic tasks. Recently, asynchronous RL has emerged as a more efficient …
Zhenyu Hou, Yujiang Li, Jie Tang, Yuxiao Dong · 📄 PDF
Stability of Flow Models for Graph Signals
Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While favorable stability properties of Graph Neural Networks (GNNs) have been well documented, it is unclear how structural errors propagate through the dyn…
Martin Schmidt, Gonzalo Mateos · 📄 PDF
Creativity from Friction: Human-AI Interaction for Exploratory Structural Design
AI agents that generate final answers based on user input often do not meet the needs of creative fields. Fields such as structural design and architecture need interactive systems that help users externalise and develop ideas, explore alternatives, and refine partial solutions. The final product of…
Ricardo Maia Avelino, Rita Sevastjanova, Tom Van Mele, Philippe Block, Mennatallah El-Assady · 📄 PDF
Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning
One-shot federated learning (OSFL) addresses the communication overhead of federated learning by limiting training to a single round, but doing so without sacrificing model quality is non-trivial, particularly when client data distributions diverge. Recent work has addressed this challenge by aggreg…
Maximilian Andreas Hoefler, Karsten Mueller, Wojciech Samek · 📄 PDF
CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis
Safety evaluation for autonomous driving is dominated by rare, safety-critical interactions, motivating simulators that can deliberately synthesize corner cases with photorealistic observations. Corner-case generation is inherently a multi-source problem spanning visual representation, scene reasoni…
Kaicong Huang, Meng Ma, Ruimin Ke · 📄 PDF
Towards Agentic AI Governance: A Preliminary Assessment
Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks. Widely characterized as the Year of Agentic AI, 2025 marked accelerated development and deployment, introducing new ethical and governance challenges. This paper pr…
Mubarak Raji, Masooda Bashir · 📄 PDF
Future Confidence Distillation in Large Language Models
Reliable confidence estimation is essential for deploying large language models (LLMs) in confidence-aware systems, where downstream decisions such as retrieval, tool use, and adaptive computation depend on accurately estimating answer reliability. Existing approaches, however, largely treat confide…
Sahil Kale · 📄 PDF
QCNN with Rough Path Signature Kernels
Time series analysis plays a vital role across a wide range of scientific and engineering domains but poses substantial computational challenges. A major difficulty arises from the time reparameterization invariance of time series data, which complicates the extraction of meaningful temporal feature…
Leonardo Nogueira Falabella, Vasily Sazonov · 📄 PDF
ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation
Deep learning has significantly advanced time series imputation, yet most existing architectures primarily rely on localized temporal context within the corrupted input sequence. This reliance can be limiting in real-world scenarios, where time series often exhibit non-stationary dynamics, weak temp…
Xuan-Thong Truong, Trung-Kien Le, Tung Kieu, Thi-Thu Nguyen, Nhat-Hai Nguyen · 📄 PDF
RL Post-Training Builds Compositional Reasoning Strategies
Does RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategies? We study this question in a fully observable rewrite-grammar environment where the pretraining distribution is known and every generated rewrite …
Azwar Abdulsalam, Nishil Patel, Andrew Saxe · 📄 PDF
Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops
AI systems increasingly participate in their own improvement: revising their outputs, adapting their own harnesses during deployment, training on data they generate, and, increasingly, conducting AI research itself. This literature is described under a vocabulary ("self-refine," "self-reward," "self…
Mingguang Chen, Licheng Wang, Bo Qu · 📄 PDF
DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation
Large language models increasingly \emph{understand} dialectal English, yet still \emph{produce} only standard, US-leaning English, leaving dialectal generation, the harder half of the problem, largely unaddressed. We introduce \textbf{DiaLLM}, which continually pretrains three open-weight language …
Jordan Painter, Dipankar Srirag, Adarsh Kappiyath, Diptesh Kanojia, Aditya Joshi, Lu Yin · 📄 PDF
SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents
Autonomous AI agents can execute complex tasks with limited human review, yet they often lack the grounded operational knowledge to make their outputs not just executable but correct, secure, and maintainable. We introduce SkillCenter, to our knowledge the largest open skill library for agents by to…
Tianming Sha, Yue Zhao, Lichao Sun, Yushun Dong · 📄 PDF
Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning
Reinforcement learning from verifiable rewards (e.g. GRPO) is the engine behind today's reasoning models, yet it grades only the final answer. On hard problems this trains models to write more rather than to think better, since the trace itself is never graded and no label for good thinking exists. …
Vladislav Beliaev · 📄 PDF
Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF
Reinforcement learning from human feedback (RLHF) has emerged as a powerful paradigm for aligning generative models with human preferences. However, applying RLHF to diffusion models remains highly feedback inefficient, as existing approaches typically require large amounts of human or reward model …
Eric Zhu, Abhinav Shrivastava, Soumik Mukhopadhyay · 📄 PDF
Institutional Red-Teaming: Deployment Rules, Not Just Models, Causally Shape Multi-Agent AI Safety
We introduce institutional red-teaming, an evaluation methodology for testing deployment rules in multi-agent AI: hold the agents, objectives, and task state fixed, vary only one rule, and attribute the resulting change in collective behavior to that rule. We instantiate the methodology in IABench-C…
Yujiao Chen · 📄 PDF
Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass
Analytical workloads operating on data stored in external database systems face a fundamental bottleneck: data access is guarded entirely by the database driver, like JDBC or ODBC, forcing all reads through query execution and other driver layers that are not designed for bulk columnar analytics. We…
Victor Giannakouris, Immanuel Trummer · 📄 PDF
Co-LMLM: Continuous-Query Limited Memory Language Models
Limited memory language models (LMLMs) externalize factual knowledge during pretraining to a knowledge base (KB), rather than memorizing it in their weights. During generation, the model then fetches knowledge from the KB as needed. This recently introduced paradigm provides multiple advantages, inc…
Yair Feldman, Linxi Zhao, Nathan Godey, Dongyoung Go, Yilun Hua, Kilian Q. Weinberger, Jennifer J. Sun, Yoav Artzi · 📄 PDF
Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning
Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge from spatial, chemical and periodic organization. Mechanistically explaining these relationships requires interpreting structural evidence through sc…
Chen Tang, Yizhou Wang, Jianyu Wu, Lintao Wang, Shixiang Tang, Pengze Li, Encheng Su, Jun Yao, Jiabei Xiao, Yuqi Shi, Ji… · 📄 PDF
Failure Privacy and Safe Collective Expression
Widely held views can go unspoken when speaking out alone invites retaliation. I recast such silence as a problem of safe coalition formation. When safety comes in numbers, there is a largest group that could speak safely. Open organizing must stay safe every step the way, making for a cascade of sp…
Matthew Cashman · 📄 PDF
From Gravity to Confinement: Wealth Redistribution as Optimal Drift Design in the Fokker-Planck Framework
A proportional wealth tax acts as a uniform gravitational field on the wealth distribution: it shifts the drift of the Fokker-Planck equation without altering the diffusion, preserving the Gini coefficient at all finite times. The same drift-shift symmetry that makes the tax non-distortionary also m…
Anders G Frøseth · 📄 PDF
Does Financial Trading Smooth Non-Convex Markets?
In non-convex markets, a competitive equilibrium may fail to exist. This turns out to be an important issue in real-world non-convex auction markets, such as electricity markets, as it complicates pricing and requires the auctioneer to resort to out-of-market discriminatory side payments to sustain …
Nicolas Stevens, Peter Cramton, Martial Toniotti · 📄 PDF
The U.S. Mortality Crisis as a Preston Curve Reversal
U.S. life expectancy stagnated and declined in the 2010s despite continued growth in real per capita income. We use Preston curves to characterize this pattern as a change in the relationship between income and longevity. Using state-level data from 1980 to 2019 and county-level data from 2000 to 20…
Ritikaa Khanna, Rourke O'Brien, Andrew Stokes, Atheendar Venkataramani, Elizabeth Wrigley-Field · 📄 PDF
Will AstroForge Collapse the PGM Market?
AstroForge seeks to mine platinum group metals (PGM) from asteroids. Asteroid reserves appear to be unlimited, and at current market price the gross margin of asteroid mining would be very high. It is natural to ask: when AstroForge successfully demonstrates economic space mining of PGM, will they c…
Robert T. Nachtrieb, Steven J. Smith · 📄 PDF
High-Accuracy Semi-Analytical Method for Solving the Problem of Electromagnetic Wave Scattering by Arbitrary Ensembles of Parallel Circular Cylinders
A method is proposed for solving the two-dimensional problem of electromagnetic wave scattering by a cluster of an arbitrary number of parallel, infinitely long, homogeneous, non-overlapping right circular cylinders. The cylinders may have arbitrary radii and complex permittivities, and their axes, …
V. V. Ternovski, M. I. Tribelsky · 📄 PDF
Impact of Courant number on the results of numerical simulating of signal propagation in non-dispersive homogeneous media
The paper is devoted to the study of the connection between the numerical dispersion arising in FDTD modeling of electromagnetic signal propagation in nondispersive homogeneous media optically different from vacuum and the Courant number in the 2D case. The main results are formulated in the form of…
P. A. Makarov, R. N. Skandakov, V. A. Ustyugov, V. I. Shcheglov · 📄 PDF
Optical Detuning Strategies for Shielded Loop Resonators
Purpose: To compare detuning performance and evaluate the power requirements of optical detuning methods, and to demonstrate the feasibility of an optically detuned four-channel receive array. Methods: Four optical detuning methods were compared in simulations, bench tests, and phantom measurements …
Jakob Gerlach, Reza Aghabagheri, Zining Liu, Shuai Liu, Morteza Teymoori, Caglar Ataman, Michael Bock, Ali Caglar Oezen · 📄 PDF
AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking
Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery. However, existing methods treat affinity comparisons independently and ignore the contextual information encoded in other labeled comparisons, limiting their ability to captur…
Zhiyuan Chen, Jing Hu, Junzhe Wang, Yueyang Huang, Xinyi Yang, Zhaoyang Wang, Feng Zhu · 📄 PDF
Characterization of DLBCL cell of origin-phenotypes based on tumor microenvironment features
Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma with a high recurrence rate. The molecular profiling of DLBCL tumors culminated in several immunohistochemistry algorithms for prognostic stratification. Among those, the Hans classifier is widely used for classifyin…
Stefano Ugliano, Martim Dias Gomes, Noémie Moreau, Marta Pistone, Marcel Kirchner, Alexandra Just, Adrian Georg Simon, C… · 📄 PDF
Compiling Bioinformatics Recurrences
Many bioinformatics algorithms, such as sequence alignment and structure prediction, can be expressed as recurrence equations over a dynamic programming matrix. Efficient implementations of these algorithms for large-scale biological data often require changing the order in which matrix cells are ca…
Bala Vinaithirthan, Shiv Sundram, Sneha Goenka, Fredrik Kjolstad · 📄 PDF
EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning
We introduce EntroPath, a manifold learning method that recovers geodesic geometry from data graphs through ensembles of diffusion paths. Many existing graph-based embeddings rely either on locally normalised random walks or on shortest-path distances. The former can concentrate diffusion in densely…
Przemysław Rola · 📄 PDF
Self-Heating and Radiation Hardness Studies of 3nm GAA-FET-Based SRAM with Different Substrate Isolation Techniques
In this work, 3D full-domain 3 nm gate-all-around field-effect transistor (GAA-FET) static random access memories (SRAMs) with various substrate isolation techniques are simulated using Technology Computer-Aided Design (TCAD). In addition to the traditional bottom dielectric isolation (BDI), which i…
Albert Lu, Junipero Verbeke, Phil Oldiges, Reza Arghavani, Hiu Yung Wong · 📄 PDF
Latency-Constrained Hardware-Aware Quantum Error Correction Co-Design with Adaptive Confidence-Gated Neural Decoding for the Rotated Surface Code
Real-time decoding is a major bottleneck in scaling quantum error correction (QEC) from noisy intermediate-scale quantum (NISQ) devices to fault-tolerant quantum computing. We present an adaptive confidence-gated decoding framework for the rotated surface code that treats decoding as a two-stage inf…
Sumit Chongder · 📄 PDF
Hybrid quantum floating-point method for sharp arithmetic
There are several possible ways to encode random variables in a quantum state. The basis encoding of bit strings has paramount importance because it allows to load the values of a random variable through the superposition of corresponding basis states, and to then exploit quantum parallelism in proc…
Gabriele Agliardi, Enrico Prati · 📄 PDF
Designing Maintainable Hybrid Generative Systems: A Quantum-Inspired Approach to Automated Music Harmony Generation
This paper presents the design and evaluation of a maintainable hybrid generative architecture for automated music harmony generation from melody. The proposed system combines quantum-inspired candidate exploration over overlapping melodic contexts with explicit rule-based optimization to balance ge…
Josef Pavlicek · 📄 PDF
Digital Fragmentation and Generative AI Use Across 103 Million Application Events
Knowledge workers switch between applications thousands of times per day, spending nearly a tenth of the work year transitioning between digital applications in a process called digital fragmentation. Whether this fragmentation reflects who an employee is, where they work, or what kind of day they a…
Sumer S. Vaid, Ashley V. Whillans · 📄 PDF
Boosting FPGA Performance with Direct BRAM-DSP Paths
Efficient data movement between memory and compute units is a key performance bottleneck in modern FPGA designs, particularly for deep learning (DL) workloads. In typical FPGA architectures, data transfers between block RAMs (BRAMs) and digital signal processing units (DSPs) must traverse the global…
Jiajun Hu, Ruthwik Reddy Sunketa, Andrew Boutros, Aman Arora · 📄 PDF
GPU-Accelerated Effective Resistance Analysis for 3D IC Power Delivery Network
Three-dimensional (3D) integration is a critical technique for enhancing transistor density, improving power efficiency, and reducing interconnect delays. However, as current demands and design complexity increase, power deliver networks (PDNs) are facing growing challenges.Careful planning of throu…
Jingchao Hu, Cheng Zhuo, Zhou Jin · 📄 PDF
Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation
This paper presents a black-box evaluation framework to systematically assess the ability of Large Language Models (LLMs) to generate Design Structure Matrices (DSMs) from structured technical documentation. Motivated by the closed-source nature of current Auto-DSM pipelines, the framework introduce…
Niels Potters, Theo Hofman · 📄 PDF
Bit2Watt: A Cyber-Physical Vulnerability Exploiting GPU Workloads Across Power and Computing Infrastructures
Modern data centers increasingly rely on large-scale GPU clusters and on-site renewable energy resources, resulting in a tightly coupled cyber-physical system between computing workloads and power-electronic-dominated grids. In this paper, we reveal Bit2Watt, a previously unexplored vulnerability in…
Zhouhao Ji, Kaikai Pan, Wenyuan Xu · 📄 PDF
HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzing
Modern processor verification struggles to reach deep architectural states due to the inefficiencies of traditional mutation-based fuzzing. We propose HiFuzz, a novel hierarchical reinforcement learning framework that replaces mutation with a structured, two-layer generation process: a Program Agent…
Ya Wang, Hanwei Fan, Zhenguo Liu, Xiaofeng Zhou, Yangdi Lyu, Jiang Xu, Wei Zhang · 📄 PDF
PIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation
Recent text-to-image models such as DALLE-3 excel at following diverse prompts yet remain blind to individual aesthetic preferences. We study personalized image generation, where models must align outputs with a user's implicit visual preferences based on a few historically preferred images and a sh…
Yuhang Wu, Shuxiang Zhang, Wee Hian Ching, Chi Zhang, Miao Liu · 📄 PDF
Analysis-by-Proxy: Localization Signals in VLMs Operating as Condition Encoders
Vision-Language Models (VLMs) are increasingly utilized as the conditioning backbone for diffusion-based image editing due to their remarkable multimodal reasoning capabilities. While standalone VLMs demonstrate strong localization capabilities, editing pipelines frequently struggle to maintain this…
Yoav Baron, Sara Dorfman, Roni Paiss, Daniel Cohen-Or, Or Patashnik · 📄 PDF
Andha-Dhun: A First Look at Audio Descriptions in Hindi
Audio Descriptions (ADs) narrate visual content for Blind and Low Vision (BLV) audiences during gaps in audiovisual media. There is growing momentum around ADs in movies and TV shows, and with mandates from India's Central Board of Film Certification (CBFC), there is a need to expand ADs beyond Engl…
Ritabrata Chakraborty, Divy Kala, Nisheeth Bhooshan Gupta, Ganji Sreeram, Pailla Balakrishna Reddy, Makarand Tapaswi · 📄 PDF
Verification of Dynamic Holographic Behavior in Identity Documents
This paper addresses the remote verification of the authenticity of Optically Variable Devices (commonly known as holograms) on identity documents. Typically placed over the cardholder's photo, these devices provide strong and easily verifiable security for human inspection but pose challenges for a…
Glen Pouliquen, Joseph Chazalon, Guillaume Chiron, Thierry Géraud, Ahmad Montaser Awal · 📄 PDF
EgoPolice: A Benchmark for Egocentric Video Understanding in High-Stakes Police Body-Worn Camera Footage
We introduce EgoPolice, a carefully curated dataset of real, egocentric police-civilian interactions, sourced from publicly available body-worn camera videos. We select police-civilian action labels that are critical for police behavioral research and annotate them at a second-by-second granularity.…
Max Gonzalez Saez-Diez, Jihoon Chung, Adam D. Wolsky, Gregory Lanzalotto, Dean Knox, Jonathan Mummolo, Brandon M. Stewar… · 📄 PDF
A VLM-Enhanced Framework for Comprehensive Traffic Sign Condition Assessment Integrating Daytime Visual Performance and Nighttime Retroreflectivity Evaluation
Traffic signs are crucial components of road safety, serving as visual tools under all lighting conditions. The Manual on Uniform Traffic Control Devices (MUTCD) specifies daytime visual factors such as legibility and color contrast, and nighttime retroreflectivity requirements. Traditional assessme…
Linlin Zhang, Neema Jakisa Owor, Xiang Yu, Abby Watts, Yaw Adu-Gyamfi · 📄 PDF
Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation
Robustness to domain shift is a key requirement for floor plan generative models to be applicable beyond the single dataset they were trained on, as floor plans vary widely across regions due to distinct architectural cultures, spatial constraints, and construction practices, while acquiring new ann…
Matthieu Ospici, Arnaud Gueze, Luc Bourrat, Adrien Bernhardt · 📄 PDF
Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles
Poisoning attacks against public datasets lead to major concerns, such as (i) misclassification of perceived objects when the poisoned data is used for training and (ii) embedding of backdoors that may eventually be triggered later on, when specific conditions in the system apply over the learned mo…
Marwan Lazrag, Badis Hammi, Lorena Gonzalez-Manzano, Joaquin Garcia-Alfaro · 📄 PDF
Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation
Evaluating end-to-end autonomous driving (E2E-AD) remains challenging, as existing driving simulation methods often trade off closed-loop interactivity (e.g., CARLA) and real-world visual fidelity (e.g., nuScenes). We present \textbf{\emph{Point as Skeleton}}, a generative sensor simulation framewor…
Songbur Wong, Xiaosong Jia, Junqi You, Bo Zhang, Pei Xu, Renqiu Xia, Yuping Qiu, Shaofeng Zhang, Zelin Zhao, Xuechao Yan… · 📄 PDF
CAIRN: Cross-Room 3D Scene Understanding with Topology-Aware Large Multimodal Models
Existing 3D scene-grounded Large Language Models (3D-LLMs) focus on answering questions grounded in simplified single-room 3D scenes, lacking the ability to reason over real-world household environments containing multiple interconnected rooms and diverse object categories. We introduce CAIRN, a top…
He Liang, Chenyang Ma, Yiming Zhang, Sangyun Shin, Andrew Markham, Niki Trigoni, Yuhang He · 📄 PDF
Unsupervised Domain Adaptation for Calcification Classification in Mammography Across Multi-Site Datasets
Deep learning-based computer-aided diagnosis (CAD) systems have shown strong performance in breast cancer diagnosis, particularly for classification tasks in mammography. However, domain shifts across multi-site datasets remain a challenge, especially when models are applied to unseen domains. In th…
Xuan Liu, Derek L. Nguyen, Emily C. Barre, Jennifer Thomas, Thomas Lynch, Jeffrey R. Marks, E. Shelley Hwang, Marc D. Ry… · 📄 PDF
MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation
Infrared remote-sensing imagery captures intensity structure, object-background contrast, and illumination-invariant cues often invisible in RGB imagery. Yet, most remote-sensing vision-language resources and models focus on visible-band semantics, leaving infrared vision-language understanding unde…
Jiaju Han, Ma Yaqi, Yahui Chai, Xuemeng Sun, Xin Li, Qike Zhang, Yingying Zhao, Xiang Chen, Luwei Yang, Chengyin Hu, Jia… · 📄 PDF
From RGB Generation to Dense Field Readout: Pixel-Space Dense Prediction with Text-to-Image Models
Large-scale text-to-image models are attractive backbones for dense prediction because RGB generation pretraining learns rich semantic, structural, and geometric priors. Existing generative and editing approaches reuse these priors by casting dense prediction as target generation: annotations such a…
Zanyi Wang, Xin Lin, Haodong Li, Dengyang Jiang, Yijiang Li, Pengtao Xie · 📄 PDF
ProxyPose: 6-DoF Pose Tracking via Video-to-Video Translation
Tracking the six-degree-of-freedom (6-DoF) pose of objects and surfaces from monocular video is a long-standing problem in computer vision. To tackle this problem, existing methods require inputs beyond the video itself-such as 3D models, depth maps, object masks, or task-specific learned features-a…
Ruihang Zhang, Felix Taubner, Pooja Ravi, Kiriakos N. Kutulakos, David B. Lindell · 📄 PDF
Vision as Unified Multimodal Generation
We formulate computer vision as unified multimodal generation, where heterogeneous visual tasks are expressed in the native text and image generation spaces of a unified multimodal model, without task-specific architectures. Under this formulation, SenseNova-Vision uses natural-language instructions…
Xiaoyang Han, Jianhua Li, Kewang Deng, Zukai Chen, Xuanke Shi, Sihan Wang, Boxuan Li, Linyan Wang, Siyi Xie, Xin You, Ji… · 📄 PDF
Lift3D-VLA: Lifting VLA Models to 3D Geometry and Dynamics-Aware Manipulation
Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in physical environments fundamentally requires geometric understanding and spatial reasoning. While some VLA approaches attempt to incorporate 3D infor…
Jiaming Liu, Qingpo Wuwu, Nuowei Han, Hao Chen, Zhuoyang Liu, Fan Fei, Yueru Jia, Chenyang Gu, Yandong Guo, Boxin Shi, S… · 📄 PDF
From Voting to Agent Collaboration: Answer-Type-Aware LLM Pipelines for BioASQ 14b
Biomedical question answering requires not only accurate extraction of information from scientific literature but also reliable integration of evidence across multiple documents. This study presents a question-type-specific large language model (LLM) framework for BioASQ 14b Task B, designed to impr…
Taeyun Roh, Eunha Lee, Wonjune Jang, Sohyun Chung, Junha Jung, Jaewoo Kang · 📄 PDF
Provable learning separation for predicting time-evolution of quantum many-body systems
Given that quantum computers are naturally suited to simulate the behavior of quantum many-body systems, an immediate question arises: can one formulate physically motivated quantum machine learning (QML) tasks that exhibit learning separations? We address this problem by studying the learnability o…
Rahul Bandyopadhyay, Riccardo Molteni, Jens Eisert, Vedran Dunjko, Sofiene Jerbi · 📄 PDF
A Physics-Informed Neural Network Framework for Elastodynamic Wave Propagation in Bimaterial Systems
Physics-informed neural networks (PINNs) provide a promising framework for solving partial differential equations while embedding the underlying physical laws directly into the learning process. This study presents a PINN-based framework for modeling transient elastodynamic wave propagation in bimat…
Sonal Ankush Chibire, Jenn-Terng Gau, Bo Zhang · 📄 PDF
Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation
We present PACR-Video, a parameter-efficient framework for multi-shot long video extrapolation that preserves recurring entities, scene structure, visual style, and causal progression without full generator fine-tuning. PACR-Video keeps a text-to-video diffusion transformer frozen and augments it wi…
Anna Córdoba, Adam Puente Tercero, Nerea Angulo Hijo, Mar Linares Tercero, Julia Barrientos, Ainhoa Miranda, Jesús Olive… · 📄 PDF
Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities
Current benchmarks for evaluating Large Language Models (LLMs) in data analysis often fail to reflect real-world settings. They typically focus on fact retrieval from small tables and overlook the challenges of large multi-tabular datasets, external knowledge integration, and exploratory insight dis…
So Hasegawa, Shailaja Keyur Sampat, Lei Liu, Wei-Peng Chen · 📄 PDF
AirflowAttack: Thermal-Airflow Adversarial Perturbations against Infrared Remote-Sensing Vision-Language Models
Vision-language models (VLMs) are increasingly deployed on infrared (IR) remote sensing imagery in security-critical settings, yet their adversarial robustness remains unexamined. We present AirflowAttack, to our knowledge the first adversarial attack for IR remote-sensing VLMs and the first to weap…
Cong Su, Jiaju Han, Xuemeng Sun, Chengyin Hu, Qike Zhang, Jiujiang Guo, Yiwei Wei, Jiahuan Long · 📄 PDF
Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms
The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers of distributed generation control are mainly focused on residential and commercial applications. To contribute to the effective integration of renew…
Marcos Eduardo Cruz Victorio, Karl Mason · 📄 PDF
Pitwall: Faithful Natural-Language Race-Strategy Briefings from a Calibrated Real-Time Monte Carlo Engine
Live sports commentary is grounded generation under a deadline: statements concern real, named athletes, the grounding state changes every few seconds, and no reference text exists at generation time. We present Pitwall, a production system that generates natural-language Formula 1 strategy briefing…
Juan S. Santillana · 📄 PDF
Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade
Large language model (LLM) agents solving multi-step tasks frequently commit to trajectories that are doomed to fail, yet continue to consume substantial inference compute before the failure becomes observable. We show that failure is predictable early from the agent's internal representations: ligh…
Kai Ruan, Zihe Huang, Ziqi Zhou, Qianshan Wei, Xuan Wang, Hao Sun · 📄 PDF
RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models
Recent years have witnessed the emergence of multivariate modeling using time series foundation models (TSFMs), which achieve advanced zero-shot generalization. Modern multivariate TSFMs are predominantly pretrained on multivariate synthetic data, which is easier to scale but may fail to capture the…
Qian Sun, Yong-Ming Tian, Jia-Wei Huang, Cheng Feng, Shao-Qun Zhang · 📄 PDF
Industry Classification of GitHub Repositories Using the North American Industry Classification System (NAICS)
GitHub hosts hundreds of millions of public repositories, but the platform exposes no native mapping from repositories to standardized industry sectors. This gap limits empirical work on the geography of innovation, the industrial composition of open-source production, and the diffusion of new techn…
Kevin Xu, Alexander Quispe · 📄 PDF
FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games
We present FootsiesGym, an open-source environment for learning in a non-trivial two-player, zero-sum, imperfect-information game. Built on HiFight's minimalist 2D fighting game Footsies, it isolates the cyclic, non-transitive strategic interactions of fighting game neutral play while remaining simp…
Chase McDonald, Nathan Tsang, Wesley N. Kerr · 📄 PDF
FreqDepthKV: Frequency-Guided Depth Sharing for Robust KV Cache Compression in Long-Context LLM Inference
Long-context LLM inference is increasingly limited by the memory and bandwidth cost of KV caches, yet aggressive compression can remove the layer-specific evidence needed for retrieval and multi-step reasoning. We introduce FreqDepthKV, an inference-time cache compression method that factorizes adja…
Anna Córdoba, Adam Puente Tercero, Nerea Angulo Hijo, Mar Linares Tercero, Julia Barrientos, Ainhoa Miranda, Jesús Olive… · 📄 PDF
Bridging Physical Reasoning and Task Generalization via Visual Action Outcome Reasoning Alignment
Vision-language models (VLMs) struggle to generalize in interactive physical reasoning, particularly under unseen tasks and environments. Two key failure modes are prominent: hallucinated chain-of-thought (CoT) reasoning that contradicts physical reality, and misalignment between the model's reasoni…
Han-Jun Ko, Jr-Jen Chen, Haobo Yuan, Hsin-Ying Lee, Tiancheng Shen, Ming-Hsuan Yang, Yu-Chiang Frank Wang · 📄 PDF
DepthWeave-KV: Token-Adaptive Cross-Layer Residual Factorization for Long-Context KV Cache Compression
Long-context language model inference is increasingly limited by the memory bandwidth and capacity required to store key-value caches, yet existing compression methods often apply uniform budgets across layers or tokens and degrade retrieval when lexical cues and semantic states require different pr…
Anna Cordoba, Adam Puente Tercero, Nerea Angulo Hijo, Mar Linares Tercero, Julia Barrientos, Ainhoa Miranda, Jesus Olive… · 📄 PDF
RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation
Multi-hop Question Answering over Knowledge Graphs faces a critical challenge: traditional retrieve-then-read pipelines break differentiability, preventing the retriever from learning to bridge the semantic gap where intermediate nodes lack lexical overlap with the query. To address this, we propose…
Sambaran Bandyopadhyay, Ananth Muppidi · 📄 PDF
The Large Cancer Assistant (LCA): A Model-Agnostic Orchestration Framework for Scalable Clinical Decision Support in Oncology
- Objective: Multimodal deep learning models in oncology are currently limited by monolithic designs that rigidly couple data ingestion, clinical routing, and artificial intelligence (AI) inference. To address this inflexibility, we propose the Large Cancer Assistant (LCA), a model-agnostic, post-ho…
Ghassen Marrakchi, Basarab Matei · 📄 PDF
Rethinking Indic AI from a Lens of Cultural Heritage Preservation
As Artificial Intelligence (AI) makes inroads into different parts of the Indian subcontinent, there is significant interest in studying how AI impacts the linguistic and cultural foundations of this civilization. AI is seen as a ''double-edged sword'' where on the one hand, it can enable access and…
Aparna Madva, Sharath Srivatsa, Srinath Srinivasa, Tulika Saha · 📄 PDF
Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion
Denoising graphs is a fundamental problem in graph learning and the core operation of graph diffusion models. Attention-based architectures like graph transformers have recently shown promise in denoising graphs. However, our principled understanding of attention-based graph denoising remains limite…
Shervin Khalafi, Igor Krawczuk, Sergio Rozada, Charilaos Kanatsoulis, Antonio G Marques, Alejandro Ribeiro · 📄 PDF
ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation
Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction remains largely implicit. Existing methods concatenate text and 3D tokens into a flat sequence and rely on self-attention, collapsing coarse structural …
Tianjiao Yu, Xinzhuo Li, Yifan Shen, Onkar Susladkar, Yuanzhe Liu, Xiaona Zhou, Ismini Lourentzou · 📄 PDF
Fooling Yourself: how narratives shape beliefs
Decision-makers usually receive information through narratives that combine diagnostic evidence with nondiagnostic details. In a laboratory experiment, we study how such nondiagnostic clues affect belief updating. Participants repeatedly report beliefs in a Bayesian inference task within a narrative…
Andrea Albertazzi, Paolo Pin, Marco Stimolo, Alessandro Stringhi · 📄 PDF
The Geography of Private Sector Agricultural Innovation in the USA: Evidence from Patents
This paper develops a novel estimates of annual private sector agricultural R&D at the level of US states for the period 1976-2014. For each of five different agricultural subsectors, I allocate estimates of national private sector R&D across the 50 states by using the geographic distribution of inv…
Matt Clancy · 📄 PDF
Non-Hermitian Dirac Vortex: Minimal Theory for Topological-Cavity Surface-Emitting Laser
We construct a non-Hermitian Dirac-vortex model that combines a complex-mass winding with an infinite-imaginary-potential boundary, extending the Jackiw-Rossi and neutrino-billiard models to the dissipative regime. Moreover, this model serves as a minimal theory for the recently proposed topological…
Zong-Liang Li, Guang-Rui Li, Le-Chen Yang, Zhong Wang, Ling Lu · 📄 PDF
Critically coupled zeroth-order resonance for ultrathin nonlinear photonics
Ultrathin active materials are essential for compact nonlinear and quantum photonic devices, yet no general principle exists to link their optical constants to the cavity designs required for simultaneous field buildup and reflection suppression. Consequently, achieving extreme optical confinement c…
Hae-Seok Jeong, Soon-Jae Lee, Young-Ho Jin, Su-Hyun Gong, Q-Han Park · 📄 PDF
All-optical control of coherent perfect absorption via frequency conversion
Coherent perfect absorption (CPA) extinguishes optical fields through interference and dissipation, but conventional implementations rely on material loss that is largely fixed after fabrication. Here we demonstrate all-optically controllable CPA based on frequency conversion in a periodically poled…
Rikizo Ikuta, Hirokazu Kobayashi, Hiroki Takahashi · 📄 PDF
Characterization of Event-Based Vision Sensors for High-Speed Optical Instrumentation
Event-based vision sensors provide asynchronous event generation and microsecond timestamp resolution, which may be useful for high-speed optical measurements. However, precise event timestamps do not necessarily guarantee accurate reconstruction of temporally varying optical signals, particularly u…
Tomás Lopes, Joana M. Teixeira, Tiago D. Ferreira, Catarina S. Monteiro, Pedro A. S. Jorge, Nuno A. Silva · 📄 PDF
Ultra-high-speed line-scan Raman imaging
Raman spectroscopic imaging has emerged as a potent tool due to its non-invasive nature and capability for chemical composition analysis. Line-scan Raman spectroscopy accelerates imaging speed by two orders of magnitude compared to point detection Raman methods. However, further enhancements in imag…
Qingyi Wu, Xusheng Tang, Francesco Masia, Peng Liang, Hao Peng, Lindong Shang, Yuntong Wang, Yue Qu, Wolfgang Langbein, … · 📄 PDF
When Reflection and Transmission Amplitude Coefficients Exceed Unity: Evanescent Waves, Resonances, and Optical Modes
The reflection and transmission of propagating harmonic waves in linear optical systems have been widely discussed in the literature and are generally well understood. In passive systems involving only propagating waves, energy conservation constrains measurable quantities such as reflectance and tr…
Raúl de la Fuente · 📄 PDF
Focusing and light collection effects on plasma-induced frequency-resolved optical switching (PI-FROSt) traces
Plasma-Induced Frequency-Resolved Optical Switching (PI-FROSt) is a promising and recently proposed phase-matching-free technique for characterising ultrafast pulses across broad spectral ranges. We investigate the mechanisms of PI-FROSt trace formation through numerical simulations and experimental…
M. Guerras, Í. J. Sola, B. Alonso, E. Conejero Jarque, I. Lopez-Quintas, J. San Roman, A. Crego · 📄 PDF
Noise-limited secret key agreement with twin optical physically unclonable functions
We investigate the use of twin optical fingerprints derived from correlated physical unclonable functions (PUFs), as a hardware-based platform for cryptographic key generation and distribution. Each fingerprint is associated with a random, yet reproducible speckle pattern, generated when coherent li…
Georgios M. Nikolopoulos · 📄 PDF
Optical switching of antiferromagnetic domains by nonreciprocal heat current
What distinguishes front from back? In physics, such directionality emerges only when an underlying symmetry is broken. Antiferromagnets that inherently break both space-inversion and time-reversal symmetries provide a striking example, exhibiting nonreciprocal optical responses that depend on the d…
Takeshi Hayashida, Shunsuke Izumikawa, Kenta Kimura, Carl S. Davies, Andrei Kirilyuk · 📄 PDF
Surface-exciton enhanced SHG response in few-layer 2H-TMDC
We explore the nonlinear optical properties of few-layer MoS2 by means of polarization and laser-power-dependent measurements as well as ab initio techniques. While for even layer samples a weak second-harmonic (SH) signal can be attributed to the presence of surface defects or interface effects, ou…
H. Hübschmann, G. Berth, M. Groll, K. Burgholzer, A. Bonanni, K. D. Jöns, U. Gerstmann, W. G. Schmidt, A. Bocchini · 📄 PDF
Two Photon excitation microscopy of individual Single-Walled Carbon Nanotubes
Two-photon fluorescence imaging achieves deep-tissue penetration through long excitation wavelengths and nonlinear excitation confinement. The 1700 nm transparency window is particularly attractive, as it optimally balances tissue scattering and absorption. However, efficient fluorophores for two-ph…
Nasim Akhtar, Marc Tondusson, Benjamin Flavel, Stéphane Bancelin, Laurent Cognet · 📄 PDF
Torsional selection rule for the spin--orbit conversion of light
Standard Pancharatnam-Berry and linear-birefringent media convert optical spin into orbital angular momentum (OAM) through an anisotropy \emph{director}, a rank-two, headless field, and therefore obey the selection rule $Δ\ell=2q$ per unit texture charge $q$. We show that a medium with geometric \em…
Edilberto O. Silva · 📄 PDF
Photon-conserving Raman soliton attractors in focusing and defocusing Kerr media
The sign of the Kerr nonlinear coefficient has long been regarded as irrelevant to the direction of the Raman-induced soliton self-frequency shift. Yet the standard generalized nonlinear Schrödinger equation (GNLSE) predicts a frequency shift that depends on the sign of the nonlinearity, which leads…
Weiye Huang, Junhong Yang, Tao Sun, Qian Gao, Peilong Yang, Jintao Fan, Günter Steinmeyer, Jinhui Yuan, Chao Mei · 📄 PDF
Calibration of systematic distortions in quantum emitter localization microscopy for deterministic nanophotonic fabrication
Quantum photonic technologies greatly benefit from quantum light emitters with high brightness, indistinguishability, and reliable polarization characteristics. Achieving optimal performance relies on the accurate localization of emitters and their deterministic integration into tailored photonic st…
Chenxi Ma, Maximilian Heller, Timon Handrup, Yiteng Zhang, Tobias M. Krieger, Thomas Oberleitner, Zenghui Jiang, Xian Zh… · 📄 PDF
Predicting Therapeutic Outcome via Aligning Patient-Specific Knowledge Graph and Gene-Level Perturbation Representations
Accurate prediction of patient-specific therapeutic response from pre-treatment transcriptomes is hindered by the scarcity of matched clinical response labels and post-treatment molecular profiles. Preclinical transfer-learning models can simulate drug-induced expression changes but are often hard t…
Dongmin Bang, Sugyun An, Inyoung Sung, Ilho Yun, Sun Kim, Sangseon Lee · 📄 PDF
Score Distributions, Not Cells: Evaluating Single-Cell Perturbations Under Class Overlap
Most classification problems assume the classes are roughly separable, so that an individual sample can usually be assigned to one class. Single-cell perturbation data violates this assumption: two perturbations can produce different populations of cells while overlapping so much that an individual …
Youssef Marrakchi, Davide D'Ascenzo, Sebastiano Cultrera di Montesano · 📄 PDF
Parenclitic hypergraphs and their application in personalized cancer therapy
Understanding the differences between individual instances of the same complex system remains a central challenge, particularly in biological contexts. Parenclitic networks constitute a suitable means to detect deviations in correlations with respect to reference populations. Here, we introduce pare…
K. K. H. Manjunatha, D. Aleja, F. Liu, M. Zhang, Y. Qi, L. Minati, G. -Q. Sun, S. Zhuang, C. Cai, J. Li, R. Criado, M. R… · 📄 PDF
Data-Driven Soft Labeling Scales DNA Read Classification to Whole-Body Cell-Type Deconvolution
Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in computational biology. Methods that rely on epigenetic marks such as DNA methylation typically operate on aggregated methylation estimates, discarding …
Dmytro Rizdvanetskyi, Nathan Ross, Pavlo Lutsik · 📄 PDF
Handover-Optimal User Association Policy for LEO Satellite-based 5G NTN
The integration of Non Terrestrial Networks into 5G and beyond cellular systems has introduced a significant paradigm shift, enabling ubiquitous connectivity and extending services to previously unconnected and underserved remote regions. In particular, Low Earth Orbit satellites, operating close to…
Pradnya Taksande, Jainesh Mehta, Prasanna Chaporkar · 📄 PDF
LLM for the development of FCM
This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that large language models, and even local large language models are capable of extracting quantities from textual data. In other words, a local LLM like Q…
Alexis Kafantaris · 📄 PDF
Optimal Base Station Placement for Beyond 5G Networks with Non-Convex Topology
This paper investigates the optimal placement of a millimeter-wave (mmWave) base station (BS) within a realistic U-shaped environment with non-convex topology. The problem is challenging and NP-hard due to the non-convex topology and the non-convex objective functions which are the sum-rate maximiza…
Mohamed Shalma, Amr Mansour, Ahmed El-Mahdy · 📄 PDF
SMART: A Machine Learning and Monte Carlo Framework for Rapid Analysis of Stochastic Transistor Aging and Process Variation in Digital Circuits
As CMOS technology scales into the deep nanometer regime, digital circuit reliability is increasingly threatened by the combined stochastic effects of Bias Temperature Instability (BTI) and Process Variation (PV). Traditional reliability analysis methods, which rely on computationally intensive simu…
Arash Esshaghi, Siavash Es'haghi, Gholamreza Shahabadi, Alireza Moradi · 📄 PDF
Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing
Computing-in-Memory (CIM) accelerators execute Matrix-Vector Multiplications (MVMs) in memory, making them a compelling solution for Machine Learning (ML) workloads. However, existing ML workload partitioning approaches for CIM accelerators do not fully account for Resistive Random Access Memory (RR…
Joel Klein, Rebecca Pelke, Roberto Laudani, Jan Moritz Joseph, Rainer Leupers · 📄 PDF
DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation
World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense supervision for robot action learning. Existing WAMs excel at physically grounded execution, but typically lack the explicit language-level planning interf…
Jian Zhu, Jianjun Zhang, Taiyi Su, Tianbin Liu, Zhangyuan Wang, Kai Xie, Zitai Huang, Chong Ma, Youzhang He, Tianjian Wa… · 📄 PDF
Closing the Reality Gap: Zero-Shot Sim-to-Real Deployment for Dexterous Force-Based Grasping and Manipulation
Human-like dexterous hands with multiple fingers offer human-level manipulation capabilities but remain difficult to train the control policies that can deploy on real hardware due to contact-rich physics and imperfect actuation. We present a sim-to-real reinforcement learning method that leverages …
Zhe Zhao, Zhibin Li, Yilin Ou, Mengshi Qi · 📄 PDF
Real-World Perturbation Testing of Autonomous Driving Systems
Autonomous Driving Systems (ADS) must operate reliably under diverse conditions, yet representative data for rare or adverse scenarios is difficult to obtain. Perturbation-based testing is widely used to assess robustness, but most studies focus on offline datasets or simulation, leaving open questi…
Stefano Carlo Lambertenghi, Matthias Weil, Andrea Stocco · 📄 PDF
Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales
Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existing approaches often address these challenges in isolation under the closed-world assumption of fixed teammates. We formalize this as open adaptive mult…
Yang Li, Feng Xue, Fan Mo, Yunhao Liu, Jianhong Wang, Ying Wen, Qingrui Zhang, Shaoshuai Mou, Wei Pan · 📄 PDF
Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control
Joint-Embedding Predictive Architectures (JEPAs) underpin a growing family of latent world models for control from raw pixels, but every existing JEPA world model commits at training time to a single inference paradigm: either trajectory optimisation in a learned dynamics model, or direct behaviour …
Ruslan Rakhimov, George Bredis, Yuriy Maksyuta, Daniil Gavrilov · 📄 PDF
Designing Touch for Trauma-Informed Social Robots: A Design Space for Direct and Indirect Actuation
Touch is a fundamental communication modality in human-robot interaction and may support grounding, emotional regulation, and stress reduction in therapeutic contexts. However, designing touch-based interactions for individuals with post-traumatic stress disorder (PTSD) requires careful consideratio…
Madeleine Rischer, Benedikt Bußmann · 📄 PDF
InternVLA-A1.5: Unifying Understanding, Latent Foresight, and Action for Compositional Generalization
Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through future prediction. In practice, existing designs tend to erode the semantics of the pretrained backbone, suffer interference among heterogeneous ob…
Haoxiang Ma, Junhao Cai, Xiaoxu Xu, Hao Li, Yuyin Yang, Yang Tian, Jiafei Cao, Hongrui Zhu, Zherui Qiu, Zhaxizhuoma, Yuq… · 📄 PDF
ECO: Incremental Ego-Centric Octree Update for Point Streams
Constructing octrees for mobile robots that process continuous point streams in real time poses significant computational and memory challenges. Standard global structures often suffer from high latency and unbalanced tree growth. We introduce the Ego-Centric Octree (ECO), a spatial data structure t…
Jaemin Yu, Seongyoon Jeong, Kang-Wook Chon, Duksu Kim · 📄 PDF
Toward Personalized Social Robots for Child Well-being: Data Requirement Principles from a Recommender-System Perspective
Social robots are increasingly deployed in clinical settings to support the well-being of children, where effective support must be personalized to each child. Personalization, choosing the robot action best suited to each child, can be framed as a recommendation problem, and a recently proposed rec…
Jin Huang, Eric Nichols, Fethiye Irmak Dogan, Hatice Gunes · 📄 PDF
Green for Go, Red for No: Visual Grounding via Semantic Segmentation for VLA Navigation Policies
Vision-language-action (VLA) models enable robot navigation from natural language and visual goals, but remain susceptible to perceptual distractions and ambiguous scene interpretations. This paper presents the first empirical evaluation of visual grounding for VLA navigation policies. We propose a …
Adrian Szvoren, Dimitrios Kanoulas, Nilufer Tuptuk · 📄 PDF
Geometry-Aware Visual Odometry for Bronchoscopic Navigation via High-Gain Observer Fusion
Navigational bronchoscopy is critical for pulmonary interventions, yet current platforms depend heavily on pre-operative CT or external sensors, limiting their use in critical care and resource-constrained settings. Vision-only navigation offers a scalable alternative, but conventional visual odomet…
Mohammadreza Kasaei, Francis Xiatian Zhang, Feng Li, Farshid Alambeigi, Kevin Dhaliwal, Mohsen Khadem · 📄 PDF
VLM-CASE: Vision-Language Model Enabled Context-Adaptive Safety Envelopes for Anticipatory Safe Autonomous Driving
Adverse driving conditions, such as bad weather, remain a principal barrier to autonomous driving because they degrade two things at once: what the vehicle can perceive and what it can physically do. Human drivers cope by anticipation, reasoning about the scene and re-budgeting speed, following dist…
Tianjia Yang, Ke Li, Ruwen Qin, Xianbiao Hu · 📄 PDF
GelNeuro: A Sensing-Computing Integrated Neuromorphic Tactile System for Texture Recognition
Neuromorphic visuo-tactile sensing offers a promising paradigm for low-latency and low-power robotic perception. However, existing systems still rely heavily on a host computer for event readout, preprocessing, or relaying prior to chip inference. This paper presents GelNeuro, a fully integrated sen…
Luoyang Bian, Xinpan Meng, Zhenghua Ma, Houcheng Li, Long Cheng · 📄 PDF
Socially-Aware Autonomous Doorway Traversal and Payload Delivery for Emergency Assistance
In this work, we focus on the scenario of a robot-assisted emergency evacuation. We consider two capabilities relevant to such a setting. The first is opening doors ahead of the people being evacuated, so that their path toward an exit stays clear. The second is retrieving rescue equipment and deliv…
Andrew Snowdy, Ananya Trivedi, Sarvesh Prajapati, Lorena Maria Genua, Taskin Padir · 📄 PDF
Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models
Training-free concept erasure is an attractive mechanism for controlling text-to-image diffusion models, but precise erasure often comes at the cost of damaging semantically related non-target concepts. Existing value-space methods remove the component of each cross-attention value along the target …
Parth Upman, Nishita Jain, Shreyank N Gowda · 📄 PDF
ChatImage: Navigating Long-Form LLM Answers through Interactive Images
Large Language Models (LLMs) can produce detailed answers to complex queries, but these answers are typically presented as dense linear text, which makes fine-grained inspection, navigation, and return visits difficult. We present ChatImage, a system that converts long-form LLM answers into interact…
Wencan Jiang, Jiangning Zhang, Yong Liu · 📄 PDF
Deep Learning for Semen Analysis in Male Infertility: Computer Vision, Multimodal Fusion, and Clinical Translation
Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and assisted reproductive technology. Conventional semen evaluation, however, is labor-intensive, operator-dependent, and limited by inter- and intra-obse…
Runwei Guan, Shaofeng Liang, Jiacheng Weng, Xiaoyi Gu, Jia Weng, Daizong Liu, Duo Pan, Qingxin Zhang, Xiao Liang, Weipin… · 📄 PDF
CenSynCMB: Centre Maps and Physics-Guided Synthesis for Microbleed Detection
Cerebral microbleeds (CMBs) are MRI markers of small vessel disease and the microbleed component of amyloid related imaging abnormalities (ARIA-H), but their small size, sparsity, and similarity to vessels, calcification-like foci, and artefacts make automated detection difficult. We propose CenSynC…
Lucas He, Hanyuan Zhang, Krinos Li, Adama Fatima Saccoh, Silvia Ingala, Rafael Rehwald, Marleen de Bruijne, Frederik Bar… · 📄 PDF
WildSplat: Feedforward Gaussian Splatting from Unposed In-the-Wild Images
While feedforward 3D reconstruction excels at efficient novel view synthesis, it typically falters when faced with scenes under varying illumination. To this end, we introduce WildSplat, the first feedforward 3D Gaussian Splatting framework capable of appearance-conditioned novel-view synthesis for …
Xiyu Zhang, Jingyu Zhuang, Hongjia Zhai, Zizheng Yan, Jinwei Chen, Guofeng Zhang, Qingnan Fan · 📄 PDF
Beyond Isolated Objects: Relationship-aware Open Vocabulary Scene Understanding via 3D Scene Graph Analysis
Open-vocabulary 3D scene understanding aims to segment 3D scenes beyond predefined categories by transferring semantic knowledge from vision-language models. Existing methods have advanced this task by lifting language-aligned 2D features into 3D, yet they often rely on context-independent semantic …
Xianhao Chen, Jiarui Hu, Yuanbo Yang, Xiyu Zhang, Tengyue Wang, Hujun Bao, Guofeng Zhang, Zhaopeng Cui · 📄 PDF
Geometric Reciprocity: Unlocking Self-Supervision for Stereoscopic Video Generation
Monocular-to-stereo conversion synthesizes stereoscopic content from 2D videos for immersive 3D experiences. In modern Depth-Image-Based Rendering (DIBR) approaches, stereo inpainting of disocclusions is the critical bottleneck. Training-based methods achieve superior quality but rely on scarce ster…
Jingyi Lu, Kai Han · 📄 PDF
ReCal3R: Reliability-Calibrated Learning Rates for Streaming 3D Reconstruction
Streaming 3D reconstruction relies on a compact recurrent scene state to process long image streams in linear time and bounded memory. However, repeated updates can gradually corrupt this state, causing reliable historical information to be overwritten by noisy or ambiguous observations. We introduc…
Xinze Li, Yiyuan Wang, Pengxu Chen, Wentao Fan, Weifeng Su, Weisi Lin, Wentao Cheng · 📄 PDF
PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space
3D reconstruction and generation are commonly tackled by separate paradigms: pixel-based regression for reconstruction, and latent diffusion for generation. Recent works attempt to unify them in latent space, but with notable drawbacks: the diffusion objective is defined on latent features rather th…
Sensen Gao, Zhaoqing Wang, Qihang Cao, Dongdong Yu, Changhu Wang, Jia-Wang Bian · 📄 PDF
MV-Forcing: Long Multi-View Video Generation via 4D-Grounded Spatio-Temporal Self-Forcing
Recent advances in video diffusion models have enabled either long single-view generation through temporal autoregression, or short multi-view synthesis through bidirectional attention. However, generating long, multi-view consistent videos of dynamic scenes remains unsolved. In this work, we presen…
Gal Fiebelman, Hadar Averbuch-Elor, Sagie Benaim · 📄 PDF
InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics
Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assumption that often fails for real-world in-the-wild videos. Consequently, estimating per-frame intrinsics from RGB images is critical for making 3D met…
Erich Liang, Caleb Kha-Uong, Chinmaya Saran, Sreemanti Dey, David W. Liu, Junhan Ouyang, Benjamin Zhou, Jia Deng · 📄 PDF
Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models
Predicting object dynamics (i.e., world modeling) is a fundamental challenge for robotic manipulation, and modeling deformable objects presents a particularly difficult case due to their high-dimensional state spaces and complex material properties. While current world models approach this through t…
Hongyu Li, Wanjia Fu, Xiaoyan Cong, Zekun Li, Binghao Huang, Hanxiao Jiang, Xintong He, Yiqing Liang, Rao Fu, Tao Lu, Sr… · 📄 PDF
SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion
We present SynCity 3000, a framework for generating 3D scenes that are globally coherent while enabling fine-grained layout control. Building on the ability of current image-to-3D generators to produce complex 3D assets from a single image, we extend this capability to the scale of entire scenes by …
Paul Engstler, Iro Laina, Christian Rupprecht, Andrea Vedaldi · 📄 PDF
Air Quality Downscaling with Station-Guided Pseudo-Supervision
Super-resolving coarse atmospheric fields to local PM$_{2.5}$ variations is uniquely challenged by a mismatch in spatial support: while pixels represent regional averages, ground-truth observations are discrete, unaligned samples of a continuous spatial signal. To bridge this gap, we present a stati…
Guorun Wang, Simone Foti, Andreas D. Demou, Leonidas Kotoulas, Theodoros Christoudias, Alexandros Koliousis, Mihalis Nic… · 📄 PDF
Learning Only What Valid Adapters Can Express: Subspace-Constrained Adaptation Against Fine-Tuning Poisoning
Parameter-efficient fine-tuning still leaves a broad space of behavior-changing updates reachable, so a poisoned objective can be represented and optimized. We study an alternative: adaptation constrained to the subspace estimated from a trusted pool of existing task adapters. On flan-t5-large with …
Fabien Polly · 📄 PDF
Biologically Informed Deep Neural Networks for Multi-Omic Integration, Pathway Activity Inference and Risk Stratification in Cancer
Integrating complex, multi-omics data presents significant challenges. Existing approaches often face a trade-off between model interpretability and representational capacity, with most either relying on post-hoc interpretation or use linear models that may overlook complex interactions. We report P…
Pedro Henrique da Costa Avelar, Le Ou-Yang, Min Wu, Sophia Tsoka · 📄 PDF
Quantum Spectral Anomaly Detection
A core task in quantum anomaly detection is to compute an anomaly score that quantifies how strongly a test quantum state deviates from a given quantum dataset assumed to be normal. Classically, principal component analysis (PCA) for centered data computes the anomaly score by evaluating the test sa…
Yewei Yuan, Michele Minervini, Mark M. Wilde, Nana Liu · 📄 PDF
How Much is Left? LLMs Linearly Encode Their Remaining Output Length
Large language models generate one token at a time, yet their responses show remarkably consistent length structure: step-by-step solutions converge in predictable token counts, retrievals stop after a few sentences, retractions extend responses by measurable amounts. We ask whether the model carrie…
Mohamed Amine Merzouk, Dmitri Carpov, Mirko Bronzi, Damiano Fornasiere, Adam Oberman · 📄 PDF
How Far is Too Far? Defining the Distance Threshold for Verification Siamese Networks
Siamese verification networks are widely used to compare items such as faces, cars, or signatures. In these scenarios, the network is trained to learn an embedding space in which similar objects are mapped closer together, while dissimilar objects are mapped further apart. Two objects are considered…
Heloísa Dias Viotto, Cauê Samonek, Lucas Garcia Pedroso, Marcos Sunye, André Abed Grégio, Paulo Lisboa de Almeida · 📄 PDF
Faithfulness to Refusal: A Causal Audit of Neuron Selectors
Attribution scores increasingly identify which neuron rows of a language model matter for applications such as pruning, interpretability, and editing for safety, yet whether they identify causally important rows is rarely tested directly. We address this with two paired audits built on one-shot neur…
Ananth Eswar, Pratinav Seth, Utsav Avaiya, Vinay Kumar Sankarapu · 📄 PDF
Fitted Occupancy-Ratio Evaluation without Bellman Completeness
Occupancy ratios correct distribution shift in offline reinforcement learning and are central to off-policy evaluation. Existing primal-dual and minimax methods typically estimate these ratios by enforcing occupancy-balance moments over a critic class. We propose fitted occupancy-ratio evaluation (F…
Lars van der Laan, Nathan Kallus · 📄 PDF
CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents
Long-horizon agentic LLMs are increasingly limited by finite context windows, as extended interaction trajectories can exceed the maximum context length before a task is completed. Context compaction offers a natural solution by summarizing previous interaction states and continuing the rollout unde…
Yujiang Li, Zhenyu Hou, Yi Jing, Jie Tang, Yuxiao Dong · 📄 PDF
TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning
In deep learning for tabular data, efficient ensembles of multilayer perceptrons (MLPs) have recently emerged as effective and practical architectures. Existing methods of this kind use the same hyperparameters for all underlying MLPs, which requires hyperparameter tuning for achieving the best perf…
Yury Gorishniy, Akim Kotelnikov, Ivan Rubachev, Artem Babenko · 📄 PDF
MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution
Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further extend this capability. However, a fixed, hand-authored skill is rarely optimal, and cannot adapt to the diversity of tasks an agent encounters. Sel…
Zefeng Wang, Minxi Yan, Jinhe Bi, Sikuan Yan, Volker Tresp, Yunpu Ma · 📄 PDF
Evaluating and Understanding Model Editing for Medical Vision Language Models
Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining. However, existing multimodal model editing benchmarks focus on general-purpose tasks and do not reflect realistic clinical domain requirements and varia…
Guli Zhu, Chenwei Wu, Liyue Shen · 📄 PDF
Topological Shape Representation for Aneurysm -- Bifurcation Detection
Automated detection of intracranial aneurysms (IAs) from CT angiography (CTA) is severely hindered by high false-positive rates. Convolutional neural networks (CNNs) rely on local pixel intensities, causing systematic confusion between saccular aneurysms and vascular bifurcations -- a problem especi…
Akshay Gokhale, Mansi Dhamne · 📄 PDF
Steering Optimisation Trajectories in Diffusion Representation Learning
We study why diffusion autoencoders can achieve similar image quality while learning substantially different latent structures. We trace this behaviour to optimisation dynamics; we analyse curves of image reconstruction against latent representation quality, revealing trajectories that organise arou…
Rajat Rasal, Avinash Kori, Tian Xia, Ben Glocker · 📄 PDF
TREK: Distill to Explore, Reinforce to Refine
Group Relative Policy Optimization (GRPO) is effective when the current policy already samples useful reasoning trajectories, but it stalls on hard prompts whose correct solution modes lie outside the student's on-policy support. We propose TREK (Teacher-Routed Exploration via Forward KL), a simple …
Yuanda Xu, Zhengze Zhou, Kayhan Behdin, Jelena Markovic-Voronov, Hejian Sang, Xiaomin Li, Wenhui Zhu, Xinchen Du, Aida R… · 📄 PDF
OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement
We propose OptiAgent, a multi-agent framework that, given a natural language description of an Operations Research problem, is able to output a solver-ready mathematical formulation as well as executable code. Our architecture prioritizes the mathematical modeling step, where dedicated agents extrac…
Adriana Laurindo Monteiro, Nayse Fagundes, Gabriel Mattos Langeloh, Gustavo de Oliveira Kanno, Priscila Louise Aguirre, … · 📄 PDF
Multiplayer Interactive World Models with Representation Autoencoders
We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world models treat the other agents as part of the environment, ours conditions on the action streams of multiple agents, learning to attribute changes in t…
Anthony Hu, Václav Volhejn, Adrien Ramanana Rahary, Chris Mulder, Aditya Makkar, Amélie Royer, Manu Orsini, Alyx Liao, A… · 📄 PDF
Selective Disclosure Watermarking for Large Language Models
Watermarking methods embed imperceptible and verifiable signals into text generated by large language models (LLMs). Existing approaches include zero-bit schemes for distinguishing synthetic text from human writing and multi-bit schemes for embedding metadata. However, current multi-bit watermarking…
Xuyang Chen, Xiang Li, Yangxinyu Xie, Qi Long · 📄 PDF
Graph Sparse Sampling: Breaking the Curse of the Horizon in Continuous MDP Planning
Planning under uncertainty in continuous domains is essential for autonomous systems, yet computationally demanding. Tree-based search methods such as Monte Carlo Tree Search (MCTS) remain popular, but their branching structure can require sampling budgets that grow exponentially with lookahead dept…
Idan Lev-Yehudi, Vadim Indelman · 📄 PDF
SovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints
Personal agents are becoming persistent user-owned intermediaries: they remember preferences, filter platform-mediated information, use tools, and negotiate with services. Existing benchmarks evaluate tool use, web navigation, desktop control, personalization, recommendation, and evolving context, b…
Dylan Zongmin Liu · 📄 PDF
REDDIT: Correcting Model-Generated Timestamp Drift in ASR without Forgetting via Replay-Based Distribution Editing
Modern autoregressive ASR systems can emit timestamps as decoded tokens, enabling timestamped transcription without frame-level aligners or inference-time post-processing. We show that these generated timestamps can drift across long non-speech spans: the transcript may remain plausible, but the dec…
Cheng-Kang Chou, Ming-To Chuang, Ke-Han Lu, Chan-Jan Hsu, Hung-yi Lee · 📄 PDF
SPEARBench: A Benchmark for Naturalness Evaluation in Streaming Speech-to-Speech Language Models
Streaming speech-to-speech language models aim to answer spoken queries directly with synthetic speech. However, standard speech and text benchmarks do not capture whether these systems behave naturally in conversations, where timing, turn-taking, prosody, interpersonal stance, language and dialect …
Thomas Thebaud, Yuzhe Wang, Hao Zhang, Sathvik Manikantan Napa Ugandhar, Ashish Hallur, Georgi Tinchev, Venkatesh Ravich… · 📄 PDF
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
For robots to work reliably in commercial and industrial applications, can recent advances in agentic coding systems combine interpretable robot programming with the open-world adaptability of model-free policies? We focus on "Variational Automation" (VA), a class of tasks that have larger variation…
Kaiyuan Chen, Shuangyu Xie, Letian Fu, Justin Yu, William Pacini, Sandeep Bajamahal, Hudson Kim, Jaimyn Drake, Daehwa Ki… · 📄 PDF
Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation
While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to their Markovian nature-relying solely on current observations. Hierarchical dual-system methods address this but suffer from a gap between high-level pl…
Jiaqi Peng, Xiqian Yu, Delin Feng, Yuqiang Yang, Wenzhe Cai, Jing Xiong, Ganlin Yang, Jinliang Zheng, Jiafei Cao, Xueyua… · 📄 PDF
What Does a Discrete Diffusion Model Learn?
What does a discrete diffusion model learn: a denoiser, a score ratio, or a bridge plug-in predictor? At the level of jump rates, these are one object in different coordinates, and reading a neural network in the wrong coordinate changes the process being trained and sampled. Starting with a rigorou…
Rodrigo Casado Noguerales, Bernhard Schölkopf, Thomas Hofmann, Aran Raoufi · 📄 PDF
Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation
Visual generators excel at rendering, but they confidently fabricate what they do not know. User requests are unbounded, evolving, and deeply long-tailed: new characters, trending entities, post-cutoff events, and more. This world-knowledge bottleneck is structural: generators are trained on fixed c…
Haozhe Wang, Weijia Feng, Jinpeng Yu, Che Liu, Ping Nie, Fangzhen Lin, Jiaming Liu, Ruihua Huang, Jimmy Lin, Wenhu Chen,… · 📄 PDF
LLM-as-a-Verifier: A General-Purpose Verification Framework
Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the ability to determine the correctness of a solution, as a new scaling axis. To unlock this and demonstrate its effectiveness…
Jacky Kwok, Shulu Li, Pranav Atreya, Yuejiang Liu, Yixing Jiang, Chelsea Finn, Marco Pavone, Ion Stoica, Azalia Mirhosei… · 📄 PDF
Interpretable Human-Label-Free Deep Learning for Real-Bogus Classification with Uncertainty Quantification
Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable labels are costly, while community labels can be noisy and survey-dependent. We aim to develop a Real-Bogus classification framework that can be trained…
Raphaël Bonnet-Guerrini, Bruno Sanchez, Dominique Fouchez, Benjamin Racine, Maya Guy, Mariam Sabalbal, Manal Yassine, Vi… · 📄 PDF
Weak-to-Strong Generalization via Direct On-Policy Distillation
Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on every new strong model because the target model must generate many rollouts during training. As models scale, post-training itself becomes a bottleneck.…
Shiyuan Feng, Huan-ang Gao, Haohan Chi, Hanlin Wu, Zhilong Zhang, Zheng Jiang, Bingxiang He, Wei-Ying Ma, Ya-Qin Zhang, … · 📄 PDF
From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model
Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing view-robust Vision-Language-Action (VLA) policies tolerate such camera variations only when the camera extrinsics are expli…
Wenhao Li, Xueying Jiang, Quanhao Qian, Deli Zhao, Shijian Lu, Gongjie Zhang, Ran Xu · 📄 PDF
The neglected contributions of Thomas C. Schelling to the economics of climate change
The rich have emitted the bulk of greenhouse gases. The poor suffer the bulk of the impacts. Climate change is a transfer from poor to rich. Climate policy is a transfer from rich to poor. Why, Schelling asked, do people in the Global North care about the descendants of people they do not care about…
Richard S. J. Tol · 📄 PDF
Strategic Information Disclosure in Algorithmic Pricing
As firms increasingly adopt AI-powered pricing algorithms, a key and urgent policy concern is how to regulate the potential algorithmic collusion. This paper approaches the regulatory question through the lens of information design and examines how different disclosure rules, committed to by a third…
Chengcheng Wang, Zexin Ye · 📄 PDF
Coherent quantum control of dark excitons in hybrid metal organic chalchogenolates
Artificial atom-like systems are a promising candidate for next generation quantum processing. Among them, dark excitons exhibit one of the longest lifetimes at high temperatures. Here, we demonstrate coherent control of dark excitonic states in metal-organic chalcogenolates (MOChas) by using an ult…
Christian L. McCoy, Tobias Saule, Mariya Aleksich, Maggie C. Willson, J. Nathan Hohman, Thomas Weinacht, George N. Gibso… · 📄 PDF
Thermal vacuum friction of objects with different dimensionality
Radiative forces acting on neutral bodies moving through a thermal bath represent a unique manifestation of the interplay between relativistic kinematics and thermal fluctuations. Vacuum friction is commonly formulated using the fluctuation--dissipation theorem or related statistical approaches, but…
Gor Chalyan, F. Javier García de Abajo · 📄 PDF
Light Coils: MRI with Fully Optical Data and Power Transmission
In MRI, dense receiver coil arrays with a high number of coil elements are used to efficiently detect and encode the signal. Further increasing the number of coils is hampered by electrical cabling and massive electronics that introduce electromagnetic coupling, integration complexity and even safet…
Zining Liu, Morteza Teymoori, Jakob Gerlach, Reza Aghabagheri, Henning Helmers, Michael Bock, Caglar Ataman, Ali Oezen · 📄 PDF
An orthogonal-to-non-orthogonal multiplexing format converter
Time-frequency orthogonality has been a foundational principle in the historical development of optical communications, whether in dense wavelength division multiplexing (WDM) within long-reach high-capacity coherent optical transmission or in time-frequency division multiple access within short-rea…
Zijian Li, Chen Ding, Zixian Wei, Qiarong Xiao, Ka-Suen Lee, Chaoran Huang, Changyuan Yu, Chester Shu · 📄 PDF
Where Does Surface $χ^{(2)}$ Come From? A Systematic Derivation of Nonlinear Surface Susceptibilities from Bulk Nonlocal Response
We extend the distributional framework developed in the companion paper [Zolla, arXiv:2605.15716] to the nonlinear case, focusing on the second-order ($χ^{(2)}$) response responsible for second-harmonic generation (SHG). Starting from the most general tensorial nonlocal second-order constitutive rel…
Zolla Frederic · 📄 PDF
Causal ASCEND: Scalable Two-tier Causal Discovery on High Dimensional Multi-omics Data
Biological systems exhibit a hierarchical structure, characterised by directed flow from upstream regulators to downstream effects. Although this ordering provides a natural scaffold for causal inference, most causal discovery and GRN methods either ignore the tiered organisation or condition on all…
Stephen Asiedu, David Watson · 📄 PDF
Spectral Diffusion for Protein Dynamics
Generative models present a promising alternative to expensive molecular dynamics for computationally querying protein dynamics, yet many existing approaches treat ensembles as unordered snapshots rather than temporally coherent trajectories, or scale poorly with protein size. We present a new physi…
Hew Phipps, Matteo Cagiada, Santiago D. Villalba, Charlotte M. Deane · 📄 PDF
A Cross-Platform Analysis of High-Performance Quantum Error Correction Codes
The theory of quantum error correction was established decades ago. Yet the limitation of the quantum computing platforms in terms of noise level and available physical qubit count persists, which greatly hinders the development of scalable quantum computing systems. In this paper, we present analyt…
Bryan Pan, Yufeng Xin · 📄 PDF
Deadline-Bound Finite-Object Delivery over Intermittent LEO Satellite Contact Plans under Residual-Service Accounting
Low-Earth-orbit (LEO) relay networks deliver finite objects -- sensing tiles, telemetry blocks, model updates, and checkpoints -- over intermittent inter-satellite and space-to-ground contact plans. Partial delivery is insufficient when the complete object misses its deadline. When an object is spli…
Houtianfu Wang, O. Tansel Baydas, Hanlin Cai, Haofan Dong, Ozgur B. Akan · 📄 PDF
Noise-Aware Synthesis of Quantum LDPC Encoder Circuits via Two-Sided Hamming Descent
Quantum low-density parity-check (LDPC) codes are a promising route to fault-tolerant quantum computation, but their use requires efficient preparation of encoded states. Standard encoder constructions generate circuits through fixed algebraic procedures, yet the resulting circuit can contain substa…
Aditya Sodhani, Keshab K. Parhi · 📄 PDF
HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference
We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on Ascend NPUs, while maintaining the online softmax state in FP16. To our knowledge, HiFA4 is the first Ascend-HIF4-targeted design of this kind evalua…
Hui Dong, Yanzhao Li, Jie Gao, Chunlu Li, Zhiyuan Zhang, Yupeng Sun, Zhenyuan Chen, Zhiqiang Zou · 📄 PDF
A Reconfigurable and Representation-Adaptive ISA-Based Architecture for Efficient DNN Acceleration
Domain-specific hardware accelerators provide significantly higher performance and energy efficiency for deep neural network (DNN) workloads than general-purpose processors, but often lack adaptability to evolving model architectures. In contrast, general-purpose ISA-based solutions, such as RISC-V-…
Vasilis Sakellariou, Vassilis Paliouras, Ioannis Kouretas, Hani Saleh, Thanos Stouraitis · 📄 PDF
Identifiability Limits of Physics-Informed Inference for Spatial Stochastic Dynamics from Static Snapshots
Despite increasing scale and resolution, many biological measurements remain destructive, revealing only spatial information rather than the dynamics it encodes. By combining flexible representations with mechanistic constraints, physics-informed machine learning offers a promising route to inferrin…
Rujie Gu, Ray Zirui Zhang, Christopher E. Miles · 📄 PDF
The Turning Point of 3D Plant Phenotyping: 3D Foundation Models Enable Minute-to-Second Cross-Crop Reconstruction and Beyond
3D plant phenotyping is notoriously known to be procedure-complicated and of low throughput due to the extensive multi-view imaging, the fragile 3D reconstruction pipeline, and the additional cost from reconstructed geometry to phenotypic extraction. These limitations are further amplified in low-co…
Hanyue Jia, Wei Zhou, Wenbo Zhou, Yanan Li, Hao Lu, Tingting Wu · 📄 PDF
Structured Gaussian Processes for Uncertainty-Aware Classification of High-Dimensional, Small-Sampled Omics Data
Classifying heterogeneous omics data remains a fundamental challenge in computational biology, particularly in high-dimensional, small-sample settings where nonlinear interactions dominate and class imbalance further complicates reliable prediction of minority phenotypes. While traditional kernel me…
Yue Zhang, Nandini Amit Gadhia, Georgios Karagiannis, Michalis Smyrnakis · 📄 PDF
Real-Time Visual Intelligence on Low-Cost UAVs: A Modular Approach for Tracking, Scanning, and Navigation
Autonomous drones are rapidly transforming modern warfare and civil applications alike. This paper presents the development of an integrated intelligent drone system designed to serve as a personal assistant. Leveraging the DJI Tello drone platform, we implemented a modular architecture that integra…
Andrei-Marian Ungureanu, Stelian Spînu · 📄 PDF
The Moving Eye: Enhancing VLA Spatial Generalization via Hybrid Dynamic Data Collection
Vision-Language-Action (VLA) models have shown remarkable promise in generalized robotic manipulation. However, their spatial generalization remains fragile. We argue that simply increasing the number of viewpoints is insufficient. Models often fall into the trap of Shortcut Learning, latching onto …
Jincheng Tang, Yilong Zhu, Zhengyuan Xie, Jiang-Jiang Liu, Jiaxing Zhang · 📄 PDF
HEFT: Heavy-Payload Full-size Humanoid Teleoperation with Privileged Motion Guidance and Windowed Payload Curriculum
General motion tracking and teleoperation offer a promising path to scalable humanoid skill acquisition, yet most existing frameworks are validated on compact platforms or without real payload interaction, leaving full-size humanoids with real payloads largely unexplored. Scaling to full-size humano…
Chenxin Liu, Qingzhou Lu, Guangxiao Yang, Xuanyang Shi, Chenghan Yang, Yanjiang Guo, Jianyu Chen · 📄 PDF
ACID: Action Consistency via Inverse Dynamics for Planning with World Models
Decision-time planning with action-conditioned world models has become a popular paradigm for embodied control. However, the standard planning cost judges a candidate solely by how close its predicted terminal state lies to the goal, leaving the realizability of the intermediate transitions unchecke…
Gawon Seo, Dongwon Kim, Suha Kwak · 📄 PDF
LIME: Learning Intent-aware Camera Motion from Egocentric Video
Autonomous robots often need to move their camera before they can act: to inspect an object, reveal an occluded region, or obtain a view that responds to a user's intent. While vision-language navigation translates instructions to base motion and vision-language-action policies map instructions to m…
Boyang Sun, Jiajie Li, Yung-Hsu Yang, Chenyangguang Zhang, Tim Engelbracht, Sunghwan Hong, Cesar Cadena, Marc Pollefeys,… · 📄 PDF
WorldSample: Closed-loop Real-robot RL with World Modelling
Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-and-error interaction beyond the states observed in demonstrations. However, deploying RL on real robots remains constrained by high interaction costs…
Yuquan Xue, Le Xu, Zeyi Liu, Zhenyu Wu, Zhengyi Gu, Xinyang Song, Bofang Jia, Ziwei Wang · 📄 PDF
Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs
Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions, and actions that are costly to collect at scale. We argue that this bottleneck stems from conflating two distinct learning objectives: acquiring phys…
Junhao Shi, Siyin Wang, Xiaopeng Yu, Li Ji, Jingjing Gong, Xipeng Qiu · 📄 PDF
Learning Agile Intruder Interception using Differentiable Quadrotor Dynamics
This paper presents a methodology for learning a control policy to intercept an intruder using the 3D direction unit vector to the intruder and the interceptor state. Prior deep reinforcement learning approaches assume either relative position or distance to the intruder is available, but this infor…
Michael Anoruo, Xiaoyu Tian, Abhishek Rathod, Timothy Naudet, Thomas Canchola, Eric Sturzinger, Kshitij Goel, Wennie Tab… · 📄 PDF
QuadRocket: An Aerial Robotic Testbed for Adaptive Thrust-Vector Control of Rocket-Like Vehicles
This paper presents QuadRocket, a quadrotor-based rocket prototype that provides a low-cost, low-risk platform for validating advanced thrust-vector control strategies for launch vehicle-type systems. The prototype consists of a cylindrical main body mounted on top of a quadrotor through a universal…
Pedro Santos, Joel Reis, Paulo Oliveira, Carlos Silvestre · 📄 PDF
Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots
Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model-specific Python stacks, backend assumptions, and robot-side glue code, especially on heterogeneous edge devices. Existing inference runtimes are de…
Ling Xu, Chuyu Han, Borui Li, Hao Wu, Shiqi Jiang, Ting Cao, Chuanyou Li, Sheng Zhong, Shuai Wang · 📄 PDF
VT-WAM: Visual-Tactile World Action Model for Contact-Rich Manipulation
Contact-rich manipulation requires policies to react to local deformation, pressure, slip, and friction, yet these cues are temporally sparse and often invisible in visual observations. Existing visual-tactile policies usually feed tactile observations directly into action prediction, but rarely mod…
Shuai Tian, Yupeng Zheng, Yuhang Zheng, Songen Gu, Yujie Zang, Yuxing Qin, Weize Li, Haoran Li, Wenchao Ding, Dongbin Zh… · 📄 PDF
Extreme Adaptive Transformer for Time Series Forecasting
Time series forecasting remains challenging when the underlying data contain rare but critical extreme events. This issue is particularly important in hydrologic forecasting, where streamflow distributions are often highly skewed and extreme peaks can have substantial impacts on flood monitoring, wa…
Sanjeev Shrestha, Hui Liu, Yifan Zhang · 📄 PDF
Optimal Stabilizer Testing and Learning with Limited Quantum Memory
We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-qubit state, but may keep only $k$ qubits of coherent quantum memory between measurements. With unrestricted memory, seminal work of Gross, Nezami and…
Srinivasan Arunachalam, Louis Schatzki · 📄 PDF
Understanding the Robustness of Distributed Self-Supervised Learning Frameworks Against Non-IID Data
Recent research has introduced distributed self-supervised learning (D-SSL) approaches to leverage vast amounts of unlabeled decentralized data. However, D-SSL faces the critical challenge of data heterogeneity, and there is limited theoretical understanding of how different D-SSL frameworks respond…
Xuanyu Chen, Nan Yang, Shuai Wang, Dong Yuan · 📄 PDF
Neuron-Aware Data Selection for Annotation-Free LLM Self-Distillation
Post-training large language models (LLMs) without real-world interaction feedback or human-labeled supervision remains challenging, particularly in specialized domains where expert annotations are costly to obtain. Recent annotation-free self-evolution methods address this by using the model's own …
Zhuowei Chen, Xiang Lorraine Li · 📄 PDF
OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers
Diffusion transformers (DiTs) achieve state-of-the-art image and video generation, but their multi-step sampling and growing parameter count make inference expensive. Post-training quantization (PTQ) is the natural remedy, yet DiT activations shift across timesteps, prompts, and guidance branches, f…
Donghyun Lee, Jitesh Chavan, Duy Nguyen, Sam Huang, Liming Jiang, Priyadarshini Panda, Timo Mertens, Saurabh Shukla · 📄 PDF
Controllable Sim Agents with Behavior Latents
Realistic traffic simulation requires agents that imitate logged behavior and can also be steered along interpretable axes. Such controllability enables engineers to isolate variables, reproduce specific edge cases, and test autonomous systems without real-world risk. We introduce Controllable Neura…
Juanwu Lu, Junyu Zhu, Ziran Wang · 📄 PDF
Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials
Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts on new architectures and datasets have led to increasingly accurate and general models, the choice of optimizer for training has largely remained unexplored, defaulting to Adam and i…
Gil Harari, Yoel Zimmermann, Ola Tangen Kulseng, Laura Zichi, Chuin Wei Tan, Marc L. Descoteaux, Boris Kozinsky · 📄 PDF
DemoPSD: Disagreement-Modulated Policy Self-Distillation
On-policy self-distillation (OPSD) has emerged as a practical method for training large language models (LLMs) to reason, where a single model acts as both the teacher and the student with different levels of information access. However, recent studies have found that the teacher's dense token-level…
Yunhe Li, Hao Shi, Wenhao Liu, Mengzhe Ruan, Hanxu Hou, Zhongxiang Dai, Shuang Qiu, Linqi Song · 📄 PDF
What LLM Agents Say When No One Is Watching: Social Structure and Latent Objective Emergence in Multi-Agent Debates
LLM agents will increasingly act in socially structured settings where role, audience, and relational context can shape what is advantageous or costly to say. We study whether such social structure, without any explicit objective in the prompt, changes what an agent expresses publicly relative to an…
Arman Ghaffarizadeh, Danyal Mohaddes, Aliakbar Izadkhah, Shahriar Noroozizadeh · 📄 PDF
Online Safety Monitoring for LLMs
Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time. Monitoring outputs online and raising an alarm when safety can no longer be assumed is therefore critical. We study a simple real-time monitor that turns a verifier signal from an external model into an al…
Mona Schirmer, Metod Jazbec, Alexander Timans, Christian Naesseth, Maja Waldron, Eric Nalisnick · 📄 PDF
Program-as-Weights: A Programming Paradigm for Fuzzy Functions
Many everyday programming tasks resist clean rule-based implementation, such as alerting on important log lines, repairing malformed JSON, or ranking search results by intent, and are increasingly outsourced to large language model APIs at the cost of locality, reproducibility, and price. We propose…
Wentao Zhang, Liliana Hotsko, Woojeong Kim, Pengyu Nie, Stuart Shieber, Yuntian Deng · 📄 PDF
LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning
LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal methods. Unlearning has emerged as a promising solution, with state-of-the-art(SOTA) methods often following a localize-first, unlearn-second paradigm th…
Matteo Boglioni, Thibault Rousset, Siva Reddy, Marius Mosbach, Verna Dankers · 📄 PDF
Exponential Sigmoid Equation for Modelling Cell Growth in a Confined Space, Log-Normal Distribution for Modelling Cell Area Distribution of Dense Colonies and Other Methods
Based on the growth patterns of 166 CHO monoclones observed over a 15 day period, we show that the standard population growth in a confined space equation, i.e. the sigmoid/logistic function, is alone does not capture the complex behaviour of the cell growth in a confined space. Thus, combining the …
Kavinda Jayawardana, Brad Turner · 📄 PDF
Effective population sizes for asymmetrically regulated birth-death processes
In multispecies birth-death processes, how population regulation -- through suppressed replication, elevated mortality, or both -- affects macroscopic stochastic dynamics has escaped detailed analysis. Here, we show that the distribution of regulation mechanisms can be invisible in deterministic or …
Yunbei Pan, Tom Chou · 📄 PDF
DRIADA: A Python Toolkit for Cross-Scale Analysis of Single-Neuron Selectivity and Population Dynamics
Brain activity spans single-neuron, population, and network levels, and core questions in neural coding require moving between them. Yet current tools target a single paradigm and incompatible data formats, leaving cross-level questions hard to address. We present DRIADA, an open-source Python frame…
Nikita Pospelov, Viktor Plusnin, Olga Rogozhnikova, Anna Ivanova, Vladimir Sotskov, Margarita Orobets, Ksenia Toropova, … · 📄 PDF
Noninvasive H3 K27M screening in pediatric diffuse midline glioma using radiomics on heterogeneous T2-weighted MRI
Histone H3K27M mutation status defines a clinically aggressive subgroup of pediatric diffuse midline glioma and informs prognosis and trial eligibility, but confirmation usually requires tissue sampling from eloquent midline structures. We evaluated whether radiomics from routinely available T2-weig…
Arthur Zagitov, Alexander Beznosikov, Vladimir Bozhenko, Ninel Kamyshnikova, Tatiana Kulinich, Sofia Polozova, Yaroslav … · 📄 PDF
Residential Battery Pooling Under Backup Commitments
Residential batteries increasingly serve two roles: they can earn money by arbitraging wholesale prices and providing grid services, and they provide backup power during outages. This dual use creates a basic tradeoff between earning market value and preserving outage readiness. Coordination across …
Jerry Anunrojwong, Baosen Zhang · 📄 PDF
Profit-Oriented Planning and Multi-Market Operation Model for Hybrid Energy Storage Systems
The increasing penetration of renewable energy necessitates improved power system flexibility, driving the deployment of independent energy storage operators (ESOs). Existing research extensively investigates capacity sizing for price-taker storage systems or the operational coordination of aggregat…
Lizhong Zhang, Junqi Liu, Jianxiao Wang, Lei Zhu · 📄 PDF
The Effects of Innovation on Foreign Portfolio Investment: The Role of Institutions and Risk-Taking
We study whether and how innovation intensity attracts foreign portfolio investment (FPI) using a panel of 60 countries from 1996 to 2021. Using an instrumental variable strategy based on regional shift-share and global push instruments, we estimate the causal response of debt and equity inflows to …
Yimin Wu, Tomoo Kikuchi · 📄 PDF
Engagement vs. Commitment: The Economic Trade-Offs of Polarizing News Content
Content that drives engagement need not be the same content that drives willingness to pay. We study how polarizing content affects engagement (time on site) and commitment (subscriptions and retention) on a major news platform. We measure article-level polarization with deep-learning classifiers an…
Shunyao Yan, Klaus M. Miller · 📄 PDF
Crosstalk-free Chiral Anomaly Bulk States in Photonic Crystals
Ultracompact cladding-free waveguide arrays with zero inter-channel spacing and negligible crosstalk open a new avenue for high-density integrated photonic circuits. However, existing cladding-free waveguide arrays typically rely on conventional trivial bulk modes, making them highly susceptible to …
Guochao Wei, Yingfeng Qi, Kang Du, Wei Zhu, Zhenzhen Liu, Junjun Xiao, Shengxiang Wang, Zhen Gao · 📄 PDF
A Wafer-Scale Heterogeneous III-V-on-Silicon Nitride Quantum Photonic Platform
Heterogeneous integration of gain and strongly nonlinear materials with ultra-low-loss silicon nitride (SiN) photonics offers a route to scalable quantum circuits, but concurrent wafer-scale manufacturability, low interlayer loss, and high performance have been challenging to realize. Here we demons…
Lillian Thiel, Boqiang Shen, Jasper R. Venneberg, Melissa A. Guidry, Nic Arnaud, Adam Slater, Lucas Wang, Xuefeng Li, Jo… · 📄 PDF
Optical Neural Networks from Coherent Transient Dynamics in Waveguide QED
Optical neural networks promise ultrafast, low-energy information processing by performing computation directly with photons. Current implementations, however, are largely restricted to steady-state operation and rely on high-latency electro-optical conversion for nonlinear activation. To address th…
Jiande Cao, Yexiong Zeng, Franco Nori, Ze-Liang Xiang · 📄 PDF
Amplification of Weak Forces via Parametric Interactions and Non-Markovian Effects in Cavity Optomechanics
Weak force amplification describes the process of amplifying a faint low-frequency signal by means of an additional high-frequency modulation, which plays a vital role in quantum sensing and high-precision measurement. However, the potential enhancement of weak-force amplification in non-Markovian e…
Y. F. Li, Ze Wang, W. Y. Hu, Yan-Hui Zhou, Cheng Shang, and H. Z. Shen · 📄 PDF
A Computationally Efficient Reciprocal Effective Roughness Model for Diffuse Scattering
Ray-tracing (RT) has become central to site-specific electromagnetic propagation modeling in dynamic complex environments. Yet its computational burden grows sharply as high-fidelity digital twins of these environments scale to millions of facets whose material parameters must be continuously update…
Giacomo Melloni, Enrico M. Vitucci, Vittorio Degli Esposti, Samuel Berweger, Jack Chuang, Camillo Gentile, Nada Golmie · 📄 PDF
Optoelectronic Chromatic Dispersion in a Single Photodiode for Machine-Learning-Based Computational Spectroscopy
Spectroscopy requires high-precision wavelength discrimination but typically requires bulky, alignment-sensitive instrumentation. To address this, we present a compact computational spectrometer built from a single germanium PN photodiode. The system exploits optoelectronic chromatic dispersion (OED…
Endalamaw Ewnu Kassa, Ziv Glasser, Uttama K. Saint, Roi Yozevitch, Shmuel Sternklar · 📄 PDF
The thin line for optical neural networks towards broad practical relevance
Optical neural networks promise unmatched efficiency, bandwidth, and latency, critical benefits as demand for neural network hardware surges. However, their practical value for general-purpose acceleration or specialized applications must be proven under application-realistic conditions. We discuss …
Anas Skalli, Daniel Brunner · 📄 PDF
Energy-Resolved Eigenmode Spectroscopy of 1-D and 2-D Non-Hermitian Skin Effects
Non-Hermitian lattices can host the non-Hermitian skin effect, a boundary-induced collapse of all bulk eigenstates into exponentially localized edge modes. This effect underlies anomalous bulk-boundary correspondence and remarkable enhancements in non-Hermitian sensing, yet direct energy-resolved ac…
Rohith Srikanth, Sashank Kaushik Sridhar, Avik Dutt · 📄 PDF
Strong nanomechanical Duffing nonlinearity and interactions induced through cavity optomechanics
Nonlinearity is a key resource in both classical and quantum signal processing. Nonlinear nanomechanical elements have found applications ranging from sensing to computing, while networks of nonlinear resonators, as well as nonlinearly coupled networks of linear resonators, constitute promising plat…
Jesse J. Slim, Ewold Verhagen · 📄 PDF
Self-healing of the Montgomery pattern
Self-healing -- the ability of a structured beam to reconstruct its transverse profile after partial obstruction -- has been demonstrated for diffraction-free beams, where the recovery distance varies continuously with obstruction size. Here, we investigate self-healing in the Montgomery pattern, a …
Athena Xu, Oscar de Vries, Alfonso Palmieri, Murat Yessenov, Ayman F. Abouraddy, Federico Capasso · 📄 PDF
Quantum Emitters at Telecommunication Wavelengths based on Carbon Defects in Transition Metal Dichalcogenides
Low-dimensional materials have emerged as promising hosts for quantum emitters, whose emission typically arises from either strain-induced band bending or defect-induced two-level systems. Among these materials, transition metal dichalcogenide (TMD) monolayers have attracted particular attention; ho…
Chanaprom Cholsuk, Sujin Suwanna, Tobias Vogl · 📄 PDF
Comparative study of second harmonic generation at 1030 nm in BiBO and LBO crystals using a 100 W-class picosecond laser
We present a systematic experimental comparison of single-pass second-harmonic generation (SHG) in bismuth triborate (BiBO) and lithium triborate (LBO) nonlinear crystals, driven by a 1.3 ps, 91 kHz laser at 1030 nm with up to 57 W of average input power. Both crystals yielded 32 W of second harmoni…
Huzefa Aliasger, Šimon Šatra, Ondřej Novák, Jiří Mužík, Michal Jelínek, Martin Smrž, Tomáš Mocek · 📄 PDF
Using a Digital Twin for Fringe Projection Profilometry Optimisation
Fringe projection profilometry (FPP) is a widely used technique for measuring object surface form and three-dimensional (3D) geometry, capable of delivering high-precision, high-resolution measurements when paired with suitable cameras and projectors. However, in practical deployments, identifying p…
D. Weston, X. Kong, G. S. D. Gordon, S. Piano · 📄 PDF
Electronic mechanism of sub-100-fs demagnetization induced by a femtosecond light pulse
A quantitative understanding of the processes that trigger light-induced demagnetization on ultrashort timescales is crucial for achieving an ultrafast, radiation-controlled magnetic response in materials. This milestone is essential for developing next-generation magnetic storage devices and ultraf…
Konrad J. Kapcia, Victor Tkachenko, Flavio Capotondi, Alexander Lichtenstein, Serguei Molodtsov, Przemysław Piekarz, Bea… · 📄 PDF
Spatiotemporal representation of a two-vortex reconnection as a single rotating vortex
Reconnections and rotations of lines are dual descriptions of the same saddle-shaped spacetime surface. We show that a reconnection between two line occurring over time is a single line that rotates over space progression. Both rotating lines and reconnections possess the same saddle shape sheet geo…
Jordan M. Adams · 📄 PDF
From order to chaos in a chip-scale Kerr parametric oscillator
Integrated photonics has enabled a wide class of chip-scale light sources and quantum technologies. Within this field, microresonator-based degenerate optical parametric oscillators (DOPOs) have gained prominence. Above a critical power threshold, these systems undergo spontaneous symmetry breaking …
Luca O. Trinchão, Juan Diego Mazo-Vásquez, Miguel Nienstedt, Luiz Peres, Julius T. Gohsrich, Eduardo S. Gonçalves, Alekh… · 📄 PDF
Detecting nonclassicality in randomly-displaced copies of a squeezed state
We address a fundamental question: Can one determine whether a received signal is squeezed when each copy arrives with a different displacement/amplitude? We introduce an interaction Hamiltonian that converts quadrature squeezing into number squeezing. Using this conversion, we test whether the copi…
Mehmet Emre Tasgin · 📄 PDF
PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference
Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor continuous trajectories are observed, so the snapshot distributions alone do not uniquely determine the underlying dynamics. Existing optimal transport and …
Chenglei Yu*, Chuanrui Wang*, Bangyan Liao, Tailin Wu · 📄 PDF
DCFold: Efficient Protein Structure Generation with Single Forward Pass
AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This state-of-the-art performance has established AlphaFold3 as a foundation model for diverse generation and design tasks. However, its iterative design sub…
Zhe Zhang, Yuanning Feng, Yuxuan Song, Keyue Qiu, Hao Zhou, Wei-Ying Ma · 📄 PDF
Protein Fold Classification at Scale: Benchmarking and Pretraining
Classifying protein topology is essential for deciphering biological function, but progress is held back by the lack of large-scale benchmarks that avoid duplicates and by models that do not scale well. We introduce TEDBench, a large-scale, non-redundant benchmark for protein fold classification con…
Dexiong Chen, Andrei Manolache, Mathias Niepert, Karsten Borgwardt · 📄 PDF
Incorporating vaccine effects into epidemiological models: common pitfalls and solutions
Incorporating vaccination into mathematical models appears deceptively simple: models integrate vaccine-derived protections, such as reduced susceptibility to infection, using parameters informed by empirical estimates of vaccine efficacy or effectiveness (VE). In practice, however, empirical VE est…
Casey E. Middleton, Oliver Eales, James M. McCaw, Freya M. Shearer · 📄 PDF
OSSMM: An Open-Source Sleep Monitor and Modulator
We present the Open-Source Sleep Monitor and Modulator (OSSMM), an open-source hardware and software platform for accessible sleep research. The OSSMM comprises a small wearable headband built from 3D prints and affordable commercial-off-the-shelf (COTS) components at a material cost under 40 euros,…
Jonny Giordano, Fergal Stapleton, Gabriel Palma, Barak A. Pearlmutter · 📄 PDF
Multi-objective Bayesian inference in an agent-based model of zebrafish patterns via topological data analysis
Spatial patterns arising from the collective behavior of individual agents are present across biological systems. While agent-based models offer a natural framework for uncovering unknown agent (e.g., cell) interactions, these stochastic models face significant challenges. For spatial patterns, agen…
Yue Liu, Alexandria Volkening · 📄 PDF
Measurement-Driven Adaptive Low-Overhead Implementation of Multi-Controlled Toffoli Gates
The Toffoli gate is a fundamental building block for quantum arithmetic and reversible logic, yet its efficient realization remains a major challenge in both near-term and fault-tolerant quantum architectures. Recent advances in dynamic quantum circuit capabilities, including mid-circuit measurement…
Abhoy Kole, Till Schnittka, Rolf Drechsler · 📄 PDF
Adaptive Clifford+T Decomposition of Large Toffoli Gates with One Clean Ancilla
Multi-controlled Toffoli gates are fundamental building blocks in quantum computation, with applications in quantum arithmetic, simulation, and search algorithms. In fault-tolerant architectures, their realization is constrained by the high cost of non-Clifford resources, particularly in terms of T-…
Abhoy Kole, Majd Assaad, Till Schnittka, Rolf Drechsler · 📄 PDF
The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaboration
Large Language Models (LLMs) are increasingly used in educational settings as interactive tools for collaboration. However, their tendency toward sycophancy, aligning with user beliefs even when incorrect, raises concerns for learning and decision-making, especially for less knowledgeable users. Thi…
Cansu Koyuturk, Sabrina Guidotti, Dimitri Ognibene · 📄 PDF
ROA-Based Subharmonic Injection Locking for Oscillator-Based Ising Machines
This paper introduces on-chip integrated rotary traveling wave oscillators (RTWOs) organized into rotary oscillator array (ROA) bricks as an external perturbation to induce subharmonic injection locking (SHIL) in oscillator-based Ising machines (OIMs). The implementation of SHILs on chip is challeng…
Nicholas Sica, Baris Taskin · 📄 PDF
CPPL: A Circuit Prompt Programming Language
Large language models (LLMs) have shown promise in register-transfer level (RTL) design automation, but direct RTL generation remains difficult to validate, optimize, and integrate with compiler-based hardware design flows. Hardware compiler infrastructures such as CIRCT provide typed intermediate r…
Shuo Yin, Yihe Wang, Lancheng Zou, Xufeng Yao, Tinghuan Chen, Chen Bai, Zhengrong Wang, Tsung-Yi Ho, Bei Yu · 📄 PDF
Enabling Agile Ambient IoT Networking via a Parameterized Hybrid Radio
The emergence of Ambient IoT signals a paradigm shift toward massive batteryless networking. However, the absence of an agile physical layer substrate remains a fundamental barrier to research and standardization. Current testbeds are hindered by decoupled radio paths, high static power, and cumbers…
Jiazhen Lei, Fengyuan Zhu, Tianze Cao, Yuxin Sha, Linling Zhong, Wenhui Li, Bingbing Wang, Zeming Yang, Jinyang Sun, Yib… · 📄 PDF
iHAC: A Hybrid Cluster Architecture for Enhanced Performance and Resilience
Uninterrupted system availability is a critical requirement for enterprise operations, yet traditional high-availability clusters suffer from limitations such as single points of failure and inefficient resource allocation. This paper introduces and evaluates the Integrated High Availability Cluster…
Siddique Abubakr Muntaka, Edward Danso Ansong, Benjamin Yankson, Oliver Kornyo, Faiza Hussein, Mohammed Nadhir Muntaka, … · 📄 PDF
Building Reliable Arithmetic Multipliers Under NBTI Aging and Process Variations
Hardware aging poses a significant challenge for integrated circuits (ICs), leading to performance degradation and eventual failure. In this work, we focus on the aging of arithmetic multipliers, which are a cornerstone of modern computing systems including in CPUs, GPUs, and FPGAs, as well as AI ac…
Masoud Heidary, Biresh Kumar Joardar · 📄 PDF
Predictive Software Scheduling as an Early-Warning Hint Layer for Optical Engine Thermal Drift in Heterogeneous SoIC Packaging
As semiconductor scaling reaches the A16 / 2 nm node, the integration of co-packaged optics (CPO) via TSMC's Co-Packaged Optics Ultra Engine (COUPE) architecture introduces critical thermal-optical coupling challenges. Micro-ring resonators embedded in the Photonic Integrated Circuit (PIC) layer are…
Chi Fei Chung · 📄 PDF
Active Defense Against False Data Injection Attacks in Robotic Manipulators
Robotic systems are vulnerable to False Data Injection Attacks (FDIAs), where adversaries corrupt sensor signals to gain malicious control. Feedback linearization exposes robotic systems to integrator vulnerability, making them susceptible to stealthy attacks that can cause significant deviations in…
Gabriele Gualandi, Carl Mikael Larsson, Alessandro V. Papadopoulos · 📄 PDF
See Silhouettes in Motion with Neuromorphic Vision
Quasi-bimodal objects, such as text, road signs, and barcodes, play a basic yet vital role in daily visual communication. By boiling these down to clear silhouettes, binarization uses a minimal language to convey essential vision cues for maximum downstream efficiency. The catch is that frame-based …
Pei Zhang, Shijie Lin, Zhou Ge, Jinpeng Chen, Wei Pu · 📄 PDF
Scenario Generation in Roundabouts with Adjustable Interaction Intensity
Roundabouts, characterized by frequent merging and yielding interactions, remain a safety-critical corner case for the development and testing of intelligent driving functions. However, extracting sufficient near-critical scenarios from naturalistic data is inefficient. Most existing scenario genera…
Li Li, Till Temmen, Tobias Brinkmann, Björn Krautwig, Markus Eisenbarth, Jakob Andert · 📄 PDF
Confidence-Gated Robot Autonomy: When Does Uncertainty Actually Help?
Robotic systems often use predictive uncertainty to decide whether to act autonomously or defer to a fallback policy. In threshold-gated autonomy, uncertainty matters mainly through its ability to rank likely errors. Standard metrics such as expected calibration error and AUROC do not directly test …
Johannes A. Gaus, Jhon P. F. Charaja, Daniel Haeufle · 📄 PDF
FUSE: A Framework for Unified State Estimation in Robotic SLAM Systems
Tightly coupled SLAM formulations under mixed-rate sensing often bind temporal processing, local geometric association, estimator formulation, and map-update policy into method-specific designs. Such binding makes it difficult to vary one design choice without re-engineering the rest of the state-es…
Wei Wu, Honglin Chen, Wenhan Cao, Yao Lyu, Jiangtao Li, Tao Zhang, Shengbo Eben Li · 📄 PDF
Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations
Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving have made important progress in studying the effects of image-level corruptions, such as adverse weather or camera degradation, on perception modules…
Zhiyuan Zhang, Zhenghao Jin, Yanlun Peng, Xianda Guo, Haoran Liu, Shaofeng Zhang, Xingjun Ma, Zuxuan Wu, Junchi Yan, Xia… · 📄 PDF
4DLidarOpen: An Open 4D FMCW Lidar Dataset for Motion-Aware Autonomous Driving
We present 4DLidarOpen, a large-scale open multi-modal dataset for autonomous driving, centered on 4D frequency-modulated continuous-wave (FMCW) Lidar sensing. Unlike conventional time-of-flight Lidar datasets that mainly provide geometric measurements, 4DLidarOpen includes point-wise radial velocit…
Kane Qian, Xin Zhao, Yining Shi, Rujun Yan, Zhengqing Pan, Kaojin Zhu, Mengmeng Yang, Kai Sun, Diange Yang, Kun Jiang · 📄 PDF
TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning
In real home deployments, household agents must often operate from a complete household scene and a situated household request, rather than from a clean task specification. Such requests require agents to identify task-relevant entities, recover intended task conditions, and resolve ordering constra…
ZhiYuan Feng, Yu Deng, Ruichuan An, Zhenhua Liu, Qixiu Li, Keming Wu, Zhiying Du, Weijie Wang, Haoxiao Wang, Shuang Chen… · 📄 PDF
Fixed External Cameras as Common Prior Maps for Active 3D Scene Graph Generation
Commonly available prior information, such as BIM models, floor plans, and remote sensing images, can provide valuable geometric and semantic context for autonomous robotic systems. In this paper, we treat observations from fixed external RGB cameras as Common Prior Maps (CPMs): wide-field views of …
Giorgia Modi, Davide Buoso, Giuseppe Averta, Daniele De Martini · 📄 PDF
RGB-only Active 3D Scene Graph Generation for Indoor Mobile Robots
Current approaches to 3D scene graph generation rely on dedicated depth sensors, such as LiDAR or RGB-D cameras, for metric 3D reconstruction. This limits deployment to specialized robotic platforms and excludes settings where only RGB cameras are available, such as fixed external infrastructure. Ex…
Giorgia Modi, Davide Buoso, Giuseppe Averta, Daniele De Martini · 📄 PDF
On Improving Multimodal Pedestrian Trajectory Prediction with CVAE: A Study on Benchmark and Robot Data
Accurate pedestrian trajectory prediction is crucial for autonomous systems operating in complex environments, such as modular buses and delivery robots in suburban or semi-structured areas. Social Spatio-Temporal Graph Convolutional Neural Networks (Social-STGCNN) have shown strong performance by m…
Yuzhou Liu, Cristina Olaverri-Monreal · 📄 PDF
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-Language-Action (VLA) models when encountering unseen real-world visual disturbances, particularly under imperfect visual conditions. In this work, …
Yiyang Fu, Chubin Zhang, Shukai Gong, Yufan Deng, Kaiwei Sun, Qiyang Min, Qibin Hou, Yansong Tang, Jianan Wang, Daquan Z… · 📄 PDF
Assessing Localization Technologies for Pedestrian Collision Avoidance
Robust pedestrian safety is crucial to the next-generation of intelligent transportation systems. Such systems rely on active pedestrian localization and predictive collision alerts. Pedestrian localization can be supported by Ultra-Wideband technology and Bluetooth 6.0, which offer high-precision r…
Joshua Varughese, Joseba Gorospe, Novel Certad, Cristina Olaverri-Monreal · 📄 PDF
PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics
World models built on recurrent state space architectures enable efficient latent imagination, yet remain physically unstructured, producing dynamics that violate conservation and dissipative principles. We introduce a unified Port-Hamiltonian framework that remedies this through three synergistic m…
Xueyu Luan, Chenwei Shi · 📄 PDF
Dynamic robotic cloth folding with efficient Koopman operator-based model predictive control
Robotic cloth folding is a challenging task, particularly when considering dynamic folding tasks, which aim at folding cloth by fast motions that leverage its dynamics. When subject to such fast motions, the complexity of cloth dynamics hinders both system identification and planning of folding traj…
Edoardo Caldarelli, Franco Coltraro, Adrià Colomé, Lorenzo Rosasco, Carme Torras · 📄 PDF
Towards Ubiquitous Mapping and Localization for Dynamic Indoor Environments
We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-D cameras strategically throughout the workspace, UbiSLAM addresses limitations commonly encountered in traditional SLAM systems, such as sensitivity …
Halim Djerroud, Nico Steyn, Olivier Rabreau, Patrick Bonnin, Abderraouf Benali · 📄 PDF
Qumus: Realization of An Embodied AI Quantum Material Experimentalist
While modern Large Language Models (LLMs) and agentic artificial intelligence (AI) have demonstrated transformative capabilities in digital domains, the realization of embodied AI capable of real-world scientific discovery remains a difficult frontier. The advancements are hindered by the inherent c…
Lihan Shi, Zhaoyi Joy Zheng, Xinzhe Juan, Yimin Wang, Ming Yin, Mayank Sengupta, Kristina Wolinski, Yanyu Jia, Jingzhi S… · 📄 PDF
REBAR: Reference Ethical Benchmark for Autonomy Readiness
As autonomous systems grow more advanced, objective metrics to evaluate their ethical and legal compliance are critical for informing end users of their limitations and ensuring accountability of those who misuse them. Current ethical embodied AI frameworks remain mostly qualitative, focusing on sys…
Jonathan Diller, David Barnes, Rebekah Bogdanoff, Rhett Collier, Roddy Collins, Keith Fieldhouse, Yonatan Gefen, Cameron… · 📄 PDF
REACT: Environment-Adaptive Architecture for Continuous Formation Navigation of Wheeled Mobile Robots
Formation control of wheeled mobile robots (WMRs) has been extensively studied due to its broad applications in fields such as logistics transportation, environmental monitoring, and search and rescue. However, most existing works mainly focus on tracking predefined formations, which limits their ad…
Jianghong Dong, Yifeng Zhang, Jiawei Wang, Mengchi Cai, Keqiang Li, Guillaume Sartoretti · 📄 PDF
Bidirectional Optical sensors for Actuation Tracking (BOAT) in soft lattice systems
The growing adoption of lattice-based structures in soft robotics creates a need for advanced sensing solutions capable of monitoring their global deformation, particularly compression and extension. In this work, we address this challenge by introducing a novel optical sensor based on two patterned…
Petr Trunin, Carolina Gay, Anderson Brazil Nardin, Trevor Exley, Diana Cafiso, Lucia Beccai · 📄 PDF
Geometry-Aware Surrogate for Real-Time Hydrodynamics Estimation of Autonomous Ground Vehicles in Amphibious Environments
Autonomous ground vehicles operating in shallow water or flood-prone terrains require dynamic models that account for hydrodynamic forces. However, the simulation and planning tools currently available either lack the physical fidelity or are too computationally expensive to run in real time. This w…
Ammar Waheed, Luke Gallantree, Zohaib Hasnain · 📄 PDF
Key-Gram: Extensible World Knowledge for Embodied Manipulation
Embodied control increasingly requires models to follow compositional language instructions while reasoning over dynamic visual states. However, current vision-language-action policies and world-action models often couple linguistic knowledge with visual computation in a shared backbone or condition…
Jingjing Fan, Siyuan Li, Botao Ren, Zhidong Deng · 📄 PDF
Not What You Asked For: Typographic Attacks in Household Robot Manipulation
Open-vocabulary embodied AI agents increasingly rely on vision-language models such as CLIP for object perception and task grounding. However, the shared embedding space that enables this flexibility introduces a structural vulnerability to typographic attacks, where printed text in a physical scene…
Ali Iranmanesh, Peng Liu · 📄 PDF
Unified Walking, Running, and Recovery for Humanoids via State-Dependent Adversarial Motion Priors
We propose a unified reinforcement learning framework that enables a single policy to perform walking, running, and fall recovery on the Unitree G1 humanoid robot, validated on physical hardware without any explicit mode-switching command at deployment. The framework extends Adversarial Motion Prior…
Yidan Lu, Yichao Zhong, Liu Zhao, Wanyue Li, Peng Lu · 📄 PDF
Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot
Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. This paper presents a comparative study of data-driven system identification methods, including N4SID, ARX, and SINDYc, for modeling a tendon-actuate…
Harald Minde Hansen, Bjørn Kåre Sæbø, Kristin Y. Pettersen, Jan Tommy Gravdahl, Mario Di Castro · 📄 PDF
Dexora: Open-source VLA for High-DoF Bimanual Dexterity
Vision-Language-Action (VLA) models have recently become a central direction in embodied AI, but current systems are restricted to either dual-gripper control or single-arm dexterous hand manipulation. While low-dimensional gripper control can often be handled with simpler methods, high-dimensional …
Zongzheng Zhang, Jingrui Pang, Zhuo Yang, Kun Li, Minwen Liao, Saining Zhang, Guoxuan Chi, Jinbang Guo, Huan-ang Gao, Mo… · 📄 PDF
StableHand: Quality-Aware Flow Matching for World-Space Dual-Hand Motion Estimation from Egocentric Video
Recovering world space 4D motion of two interacting hands from egocentric video is a fundamental capability for supervising robot policy learning, where wrist trajectories track the end-effector and finger articulations specify the grasp pose. Two major challenges arise in this setting: hands freque…
Huajian Zeng, Chaohua Yao, Yuantai Zhang, Jiaqi Yang, Rolandos Alexandros Potamias, Xingxing Zuo · 📄 PDF
OmniPro: A Comprehensive Benchmark for Omni-Proactive Streaming Video Understanding
Omni-proactive streaming video understanding, i.e., autonomously deciding when to speak and what to say from continuous audio-visual streams, is an emerging capability of omni-modal large language models. Existing benchmarks fall short in three key aspects: they rely primarily on visual signals, ado…
Ruixiang Zhao, Jie Yang, Zijie Xin, Tianyi Wang, Fengyun Rao, Jing LYU, Xirong Li · 📄 PDF
Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling
Transformer-based models have advanced feedforward novel view synthesis (NVS). Current architectures such as GS-LRM and LVSM mix semantic information (e.g., RGB) and spatial information (e.g., Plücker rays) into a shared feature space. Since Plücker rays naturally carry lattice-like spatial structur…
Yihang Wu, Yihang Sun, Shaofeng Zhang, Zuxuan Wu, Junchi Yan, Xiaosong Jia, Yu-gang Jiang · 📄 PDF
Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models
Modern interactive video world models have achieved impressive visual fidelity, yet lack fine-grained multi-entity control and cross-entity, cross-world generalization. We trace this gap to the action interface: standard control protocols (e.g. animation IDs, device inputs, scene-level captions) bin…
Shangwen Zhu, Qianyu Peng, Zhao Pu, Zhilei Shu, Xiangrui Ke, Zhaohu Xing, Zizhao Tong, Zeqing Wang, Xinyu Cui, Huangji W… · 📄 PDF
Starve to Perceive: Taming Lazy Perception in VLMs with Constrained Visual Bandwidth
Vision-Language Models (VLMs) deployed as situated agents in high-resolution visual environments require active perception -- the ability to dynamically decide where to look through operations like zooming, cropping, and panning. However, current training paradigms produce models that mimic the surf…
Yuhuan Wu, Cong Wei, Fangzhen Lin, Wenhu Chen, Haozhe Wang · 📄 PDF
Dance Across Shifts: Forward-Facilitation Continual Test-Time Adaptation through Dynamic Style Bridging
Continual Test-Time Adaptation (CTTA) aims to empower perception systems to handle dynamic distribution shifts encountered after deployment. Existing methods predominantly follow a backward-alignment paradigm, which rigidly aligns incoming data with supervisory surrogates derived from the source dom…
Zhilin Zhu, Yabin Wang, Zhiheng Ma, Yaguang Song, Yaowei Wang, Xiaopeng Hong · 📄 PDF
CATA: Continual Machine Unlearning via Conflict-Averse Task Arithmetic
Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applications. However, their large-scale training data inevitably raises concerns about privacy, copyright, and undesirable content, creating a strong need …
Shen Lin, Junhao Dong, Rongjie Chen, Xiaoyu Zhang, Li Xu, Xiaofeng Chen · 📄 PDF
ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics
Most existing vision-language manipulation research targets rigid robotic arms, whose fixed morphology limits adaptability in cluttered or confined spaces. Soft robotic arms offer an appealing alternative due to their deformability, but confront challenges such as unreliable proprioception and distr…
Ziyu Wei, Luting Wang, Chen Gao, Li Wen, Si Liu · 📄 PDF
CrossView Suite: Harnessing Cross-view Spatial Intelligence of MLLMs with Dataset, Model and Benchmark
Spatial intelligence requires multimodal large language models (MLLMs) to move beyond single-view perception and reason consistently about objects, visibility, geometry, and interactions across multiple viewpoints. However, progress in cross-view reasoning remains limited by three major gaps: the sc…
Wei Wang, Yuqian Yuan, Tianwei Lin, Wenqiao Zhang, Siliang Tang, Jun Xiao, Yueting Zhuang · 📄 PDF
SPIKE: An Adaptive Dual Controller Framework for Cost-Efficient Long-Horizon Game Agents
Long-horizon multimodal agents in open-world games must stay goal-directed across many low-level interactions under tight token and latency budgets. Existing approaches often trade off costly per-step reasoning against reactive execution that can drift, repeat failures, and recover poorly. Our key i…
Wencan Jiang, Jiangning Zhang, Jianbiao Mei, Jinzhuo Liu, Yu Yang, Xiaobin Hu, Zhucun Xue, Yong Liu, Dacheng Tao · 📄 PDF
Leveraging Latent Visual Reasoning in Silence
Latent visual reasoning involves visual evidence more directly in multimodal reasoning by inserting continuous latent tokens before textual generation. However, the necessity of these latent tokens at inference remains ambiguous. We show that replacing latent tokens with random noise or removing the…
Dongyao Zhu, Zhen Wang, Xi Xiao, Han Jiang, Saeed Vahidian, Wei-Lun Chao, Tanya Berger-Wolf, Yu Su, Raju Vatsavai, Jiany… · 📄 PDF
Articulation in Prime: Primitive-Based Articulated Object Understanding from a Single Casual Video
Retrieving the 3D kinematics of articulated objects from monocular video is a fundamental challenge in computer vision. Existing methods rely on complex video setups or cues such as long-term point tracking or wide-baseline matching, but are frequently brittle under severe occlusions, rapid camera e…
Arslan Artykov, Tom Ravaud, Nicolás Violante-Grezzi, Vincent Lepetit · 📄 PDF
MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents
Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require maintaining task state across many interface transitions. Existing agents typically rely on raw history replay or text-only memory, which either over…
Ziyun Zeng, Hang Hua, Bocheng Zou, Mu Cai, Rogerio Feris, Jiebo Luo · 📄 PDF
CMAG: Concept-Scaffolded Retrieval for Marketplace Avatar Generation
Metaverse platforms rely on creator-driven marketplaces where avatars are assembled from discrete, taxonomy-labeled 3D assets (e.g., tops, bottoms, shoes, accessories) under strict category and topology constraints. While users increasingly expect free-form text control, text-only retrieval is britt…
Rajeev Goel, Jason Ding, Phani Harish Wajjala, Pavan Turaga, Tejaswi Gowda, Krishna C. Garikipati · 📄 PDF
A Large-Scale Study on the Accuracy vs Cost Trade-offs of Training and Evaluation Settings in Fine-Grained Image Recognition
Prior work on fine-grained image recognition (FGIR) has established the importance of the backbone selection, but has neglected the accuracy-vs-cost trade-offs under different training and evaluation settings. In this work we conduct a large-scale study with over 2000 experiments across 6 training a…
Edwin Arkel Rios, Augusto Christian Surya, Oswin Gosal, Fernando Mikael, Mary Madeline Nicole, Kisoon Jang, Bo-Cheng Lai… · 📄 PDF
SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training
Diffusion models have been widely studied for removing unsafe content learned during pre-training. Existing methods require expensive supervised data, either unsafe-text paired with safe-image groundtruth or negative/positive image pairs, making them impractical to scale. Furthermore, offline reinfo…
Komal Kumar, Ankan Deria, Abhishek Basu, Fahad Shamshad, Hisham Cholakkal, Karthik Nandakumar · 📄 PDF
Robo-Cortex: A Self-Evolving Embodied Agent via Dual-Grain Cognitive Memory and Autonomous Knowledge Induction
The ability to navigate and interact with complex environments is central to real-world embodied agents, yet navigation in unseen environments remains challenging due to "experiential amnesia," where existing trajectory-driven or reactive policies fail to synthesize generalizable strategies from pas…
Nga Teng Chan, Yi Zhang, Yechi Liu, Renwen Cui, Fanhu Zeng, Zeyuan Ding, Xiancong Ren, Zhang Zhang, Qifeng Chen, Jian Li… · 📄 PDF
Advancing Narrative Long Video Generation via Training-Free Identity-Aware Memory
Autoregressive video generation has improved rapidly in visual fidelity and interactivity, but it still suffers from long-term inconsistency and memory degradation. Most existing solutions either compress historical frames using predefined strategies or retrieve keyframes based on coarse implicit at…
Jinzhuo Liu, Jiangning Zhang, Wencan Jiang, Yabiao Wang, Dingkang Liang, Zhucun Xue, Ran Yi, Yong Liu · 📄 PDF
EgoExoMem: Cross-View Memory Reasoning over Synchronized Egocentric and Exocentric Videos
Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human recall from both field and observer perspectives, we introduce EgoExoMem, the first benchmark for cross-view memory reasoning over synchronized egocen…
Ruiping Liu, Junwei Zheng, Yufan Chen, Di Wen, Shaofang Quan, Chengzhi Wu, Jiaming Zhang, Kailun Yang, Kunyu Peng, Raine… · 📄 PDF
Spectral Progressive Diffusion for Efficient Image and Video Generation
Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are generated earlier in the denoising process while high-frequency details emerge only in later timesteps. This structure offers a natural opportunity for …
Howard Xiao, Brian Chao, Lior Yariv, Gordon Wetzstein · 📄 PDF
LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation
We present LongLive-2.0, an NVFP4-based parallel infrastructure throughout the full training and inference workflow of long video generation, addressing speed and memory bottlenecks. For training, we introduce sequence-parallel autoregressive (AR) training, instantiated as Balanced SP, which co-desi…
Yukang Chen, Luozhou Wang, Wei Huang, Shuai Yang, Bohan Zhang, Yicheng Xiao, Ruihang Chu, Weian Mao, Qixin Hu, Shaoteng … · 📄 PDF
Aurora: Unified Video Editing with a Tool-Using Agent
Recent video editing models have converged on a unified conditioning design: a single diffusion transformer jointly consumes text, source video, and reference images, and one set of weights covers replacement, removal, style transfer, and reference-driven insertion. The design is flexible, but it as…
Yongsheng Yu, Ziyun Zeng, Zhiyuan Xiao, Zhenghong Zhou, Hang Hua, Wei Xiong, Jiebo Luo · 📄 PDF
WavFlow: Audio Generation in Waveform Space
Modern audio generation predominantly relies on latent-space compression, introducing additional complexity and potential information loss. In this work, we challenge this paradigm with WavFlow, a framework that generates high-fidelity audio directly in raw waveform space without intermediate repres…
Feiyan Zhou, Luyuan Wang, Shoufa Chen, Zhe Wang, Zhiheng Liu, Yuren Cong, Xiaohui Zhang, Fanny Yang, Belinda Zeng · 📄 PDF
Can These Views Be One Scene? Evaluating Multiview 3D Consistency when 3D Foundation Models Hallucinate
Multiview 3D evaluation assumes that the images being scored are observations of one static 3D scene. This assumption can fail in NVS and sparse-view reconstruction: inputs or generated outputs may contain artifacts, outlier frames, repeated views, or noise, yet still receive high 3D consistency sco…
Soumava Paul, Prakhar Kaushik, Alan Yuille · 📄 PDF
Learning to Look Benign: Targeted Evasion of Malware Detectors via API Import Injection
Machine learning-based malware detectors are widely deployed in antivirus and endpoint detection systems, yet their reliance on static features makes them vulnerable to adversarial manipulation. This paper investigates whether a malware sample can be intentionally misclassified as a specific benign …
Juozas Dautartas, Olga Kurasova, Juozapas Rokas Čypas, Viktor Medvedev · 📄 PDF
Aligned Training: A Parameter-Free Method to Improve Feature Quality and Stability of Sparse Autoencoders (SAE)
Sparse autoencoders (SAEs) are one of the main methods to interpret the inner workings of deep neural networks (DNNs), decomposing activations into higher-dimensional features. However, they exhibit critical shortcomings where a large fraction of features are never activated and are unstable. Despit…
Michał Brzozowski, Neo Christopher Chung · 📄 PDF
Efficient and Noise-Tolerant PAC Learning of Multiclass Linear Classifiers
Noise-tolerant PAC learning of linear models has been of central interests in machine learning community since the last century. In recent years, many computationally-efficient algorithms have been proposed for the problem of learning linear threshold functions under multiple noise models. Yet, when…
Rita Adhikari, Shiwei Zeng · 📄 PDF
A No-Defense Defense Against Gradient-Based Adversarial Attacks on ML-NIDS: Is Less More?
Gradient-based adversarial attacks subtly manipulate inputs of Machine Learning (ML) models to induce incorrect predictions. This paper investigates whether careful architectural choices alone can yield an inherently robust Deep Neural Network (DNN)-based Network Intrusion Detection Systems (NIDS), …
Mohamed elShehaby, Ashraf Matrawy · 📄 PDF
Better Together: Evaluating the Complementarity of Earth Embedding Models
Earth embedding models transform Earth observation data into embeddings uniquely tied to locations on the Earth's surface. These models are typically evaluated in isolation, comparing the downstream task performance across different Earth embeddings. However, spatially aligned embeddings can natural…
Thijs L van der Plas, Jacob JW Bakermans, Vishal Nedungadi, Gabrielė Tijūnaitytė, Marc Rußwurm, Ioannis N Athanasiadis · 📄 PDF
Can machine learning for quantum-gas experiments be explainable?
Virtually all aspects of many-body atomic physics are challenging: experiments are technically demanding, datasets have become enormous, and the memory and CPU requirements for classical simulation of generic quantum systems often scale exponentially with system size. Machine learning (ML) methods a…
I. B. Spielman amd J. P. Zwolak · 📄 PDF
Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad
Many tasks in modern machine learning are observed to involve heavy-tailed gradient noise during the optimization process. To manage this realistic and challenging setting, new mechanisms, such as gradient clipping and gradient normalization, have been introduced to ensure the convergence of first-o…
Zijian Liu · 📄 PDF
Learning Normal Representations for Blood Biomarkers
Blood-based biomarkers underpin clinical diagnosis and management, yet their interpretation relies largely on fixed population reference intervals that ignore stable, intra-patient variability. As such, population-based interpretation can mask meaningful deviation from an individual's baseline, risk…
Aashna P. Shah, Michelle M. Li, Yash Lal, Seffi Cohen, Liat F. Antwarg, Morgan Sanchez, James A. Diao, Chirag J. Patel, … · 📄 PDF
EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL
Equipping LLMs with tool-use capabilities via Agentic Reinforcement Learning (Agentic RL) is bottlenecked by two challenges: the lack of scalable, robust execution environments and the scarcity of realistic training data that captures implicit human reasoning. Existing approaches depend on costly re…
Minrui Xu, Zilin Wang, Mengyi DENG, Zhiwei Li, Zhicheng Yang, Xiao Zhu, Yinhong Liu, Boyu Zhu, Baiyu Huang, Chao Chen, H… · 📄 PDF
Learned Memory Attenuation in Sage-Husa Kalman Filters for Robust UAV State Estimation
Unmanned Aerial Vehicles in dynamic environments face telemetry outages, structural vibrations, and regime-dependent noise that invalidate the stationary covariance assumptions of classical Kalman filters. The Sage-Husa Kalman Filter (SHKF) estimates noise statistics online, but its reliance on a st…
Kenan Majewski, Marcin Żugaj · 📄 PDF
General Preference Reinforcement Learning
Post-training has split large language model (LLM) alignment into two largely disconnected tracks. Online reinforcement learning (RL) with verifiable rewards drives emergent reasoning on math and code but depends on a programmatic verifier that cannot reach open-ended tasks, while preference optimiz…
Muhammad Umer, Muhammad Ahmed Mohsin, Ahsan Bilal, Arslan Chaudhry, Andreas Haupt, Sanmi Koyejo, Emily Fox, John M. Ciof… · 📄 PDF
PIXLRelight: Controllable Relighting via Intrinsic Conditioning
We present PIXLRelight, a feed-forward approach for physically controllable single-image relighting. Existing methods either provide limited lighting control (e.g. through text or environment maps), accumulate errors when chaining inverse and forward rendering, or require costly per-image optimizati…
Miguel Farinha, Ronald Clark · 📄 PDF
SURGE: Approximation-free Training Free Particle Filter for Diffusion Surrogate
Diffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve sample quality on task-specific objectives. However, most existing techniques require repeated score or gradient evaluations, introducing bias, high compu…
Lifu Wei, Yinuo Ren, Naichen Shi, Yiping Lu · 📄 PDF
A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability
Pipeline parallelism is a key technique for scaling large-model training, but modern workloads exhibit runtime variability in computation and communication. Existing pipeline systems typically consume static, profiled, or adaptively generated schedules as pre-committed execution orders. When realize…
Ruitao Liu, Xinyang Tian, Shuo Chen, Tingrui Zhang, Guang Yang, Alan Zhao, Wei Xu · 📄 PDF
SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science
Large Language Models (LLMs) are increasingly deployed as scientific AI as- sistants, and a growing body of benchmarks evaluates their capabilities across knowledge retrieval, reasoning, code generation, and tool use. These evaluations, however, typically assume the scientific problem is already wel…
Nithin Somasekharan, Youssef Hassan, Shiyao Lin, Gihan Panapitiya, Patrick Emami, Anurag Acharya, Sameera Horawalavithan… · 📄 PDF
Position: Weight Space Should Be a First-Class Generative AI Modality
Neural network checkpoints have quietly become a large-scale data resource: millions of trained weight vectors now exist, each encoding task-, domain-, and architecture-specific knowledge. This position paper argues that model checkpoints should be treated as a first-class data modality, and that ge…
Zhangyang Wang, Peihao Wang, Kai Wang · 📄 PDF
Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models
Credit default prediction is a tabular learning problem with severe class imbalance, heterogeneous features, and tight latency budgets. Tabular Foundation Models (TFMs) approach this problem through in-context learning, which makes their predictions sensitive to how the context window is built. We b…
Aditya Tanna, Mitul Solanki, Mohamed Bouadi, Nassim Bouarour, Pratinav Seth, Vinay Kumar Sankarapu · 📄 PDF
Post-Trained MoE Can Skip Half Experts via Self-Distillation
Mixture-of-Experts (MoE) scales language models efficiently through sparse expert activation, and its dynamic variant further reduces computation by adjusting the activated experts in an input-dependent manner. Existing dynamic MoE methods usually rely on pre-training from scratch or task-specific a…
Xingtai Lv, Li Sheng, Kaiyan Zhang, Yichen You, Siyan Gao, Xueheng Luo, Yuxin Zuo, Yuchen Fan, Junlin Yang, Ganqu Cui, B… · 📄 PDF
An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration
Central to human-aligned AI is understanding the benefits of human-elicited labels over synthetic alternatives. While human soft-labels improve calibration by capturing uncertainty, prior studies conflate these benefits with the implicit correction of mislabeled data (mode shifts), obscuring true ef…
Maja Pavlovic, Silviu Paun, Massimo Poesio · 📄 PDF
Pocket Foundation Models: Distilling TFMs into CPU-Ready Gradient-Boosted Trees
A fraud scorer needs to answer in under 2 ms. The best tabular foundation models (TFMs) take 151-1,275 ms on GPU. We close this gap by distilling the TFM offline into an XGBoost or CatBoost student that runs natively on CPU. The central obstacle is specific to in-context learning (ICL) teachers: the…
Aditya Tanna, Nassim Bouarour, Mohamed Bouadi, Vinay kumar Sankarapu, Pratinav Seth · 📄 PDF
Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
Federated Learning is a leading framework for training ML and AI models collaboratively across numerous user devices or databases. We study the trade-offs among estimation accuracy, privacy constraints, and communication cost for differentially private (DP) federated M estimation. The two standard m…
Arnab Auddy, Xiangni Peng, Subhadeep Paul · 📄 PDF
KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture
Time Series Foundation Models (TSFMs) have demonstrated notable success in general-purpose forecasting tasks; however, their adaptation to specialized classification problems remains constrained by the computational bottleneck of standard attention and the systematic omission of classical statistica…
Luis Balderas, José Alberto Rodríguez, Miguel Lastra, Antonio Arauzo-Azofra, José M. Benítez · 📄 PDF