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Optimal VC Dimension of Contrastive Learning with Margin

arXiv:2609.38834v1 Announce Type: cross Abstract: Contrastive learning is a successful paradigm for learning d-dimensional geometric representations from a collection of ``anchor--positive--negative''

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Optimize, Learn, Refine: Whole-Body Grasping and Pick-and-Throw with a Spiral Soft Robot

DGX agent

arXiv:2609.38202v1 Announce Type: new Abstract: Soft continuum robots can exploit distributed compliance for whole-body manipulation, but synthesizing behavior through changing contacts remains diffic

safetyarxiv-cs-ro

1 Oct 2026

OPTS-TTPO: Enhancing Finite-Sample Policy-Gradient Learning with Tree Search

arXiv:2609.40035v1 Announce Type: new Abstract: The policy-gradient theorem gives the exact gradient under the current policy, but finite on-policy samples may miss rare high-return trajectories. We s

safetyarxiv-cs-cl

OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software

arXiv:2609.39903v1 Announce Type: new Abstract: Scientific software presents a demanding test for computer-using agents based on visual language models (VLMs): completing a research workflow requires

Out-of-Distribution Detection using Counterfactual Distance

arXiv:2508.10148v2 Announce Type: replace-cross Abstract: Accurate and explainable out-of-distribution (OOD) detection is required to use machine learning systems safely. Previous work has shown that

Over-Personalization Is a Decision Failure: Generation-Induced Apply Bias in LLMs

arXiv:2609.34284v2 Announce Type: replace Abstract: Personalized LLMs must decide, for each stored preference, whether the current context calls for applying or suppressing it, which we call its appli

safetyarxiv-cs-cl

Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation

arXiv:2604.02543v2 Announce Type: replace Abstract: As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than accuracy is required: knowing when to trust their

OverdoseMoE: A Multi-Expert Framework for Opioid Overdose Risk Prediction

model-releasesarxiv-cs-cl

arXiv:2609.40108v1 Announce Type: new Abstract: Opioid overdose remains a major clinical and public health burden, highlighting the need for scalable approaches to identify patients at high risk. Here

OverForge: Reasoning Through Strategies and Tactics Helps Cooperative Lifelong Adaptation

arXiv:2609.39727v1 Announce Type: new Abstract: Cooperative language-model agents must coordinate over long horizons and adapt to changing environments and to partners with unfamiliar conventions, yet

agentsarxiv-cs-ai

Overlap, Unique and Conflict: Can LLMs Extract What They Can Recognize?

model-releasesarxiv-cs-cl

arXiv:2609.38799v1 Announce Type: new Abstract: Understanding multi-perspective alternative narratives requires identifying how their information agrees, conflicts, or differs across sources. Existing

Overview of BioASQ 2026: The fourteenth BioASQ Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

arXiv:2609.39975v1 Announce Type: cross Abstract: This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluati

Tutorials

P-SRM: Selective Recovery of Rejected Predictions in Visual Tracking

arXiv:2609.39832v1 Announce Type: new Abstract: Many visual tracking methods use rejection mechanisms to suppress unreliable predictions. However, these mechanisms can also reject correctly localized

tutorialsarxiv-cs-cv

Tutorials

PAMI: Part Anchored Motion for Text to Human-Object Interaction Generation

arXiv:2609.38466v1 Announce Type: new Abstract: Text-conditioned full-body human-object interaction (HOI) generation requires synthesizing human motion and object trajectories that match the input tex

tutorialsarxiv-cs-cv

PANDA: A Decentralized Architecture with Flexible Orchestration for Scalable, Fault-Tolerant Multi-Agent Systems

arXiv:2609.38482v1 Announce Type: cross Abstract: Existing architectures for LLM-based multi-agent systems (MAS) cannot reliably and efficiently solve multi-step tasks at scale: they struggle to suppo

Parameter symmetries determine representational geometry in overparameterized nonlinear networks

arXiv:2609.39078v1 Announce Type: new Abstract: Representations are routinely used across machine learning, psychology, and neuroscience to draw inferences about the computations of biological and art

Parameterization method of reservoir properties for ensemble-based data assimilation using intermediate latent space of StyleGAN

arXiv:2609.39626v1 Announce Type: cross Abstract: Ensemble smoothers are the most successful and efficient techniques currently available for history matching. However, because these methods rely on G

Hardware

PARK: Accurate Block Retrieval for Sparse Attention in Video Diffusion Transformers

arXiv:2609.38978v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a dominant architecture for video generation, but their efficiency is limited by the quadratic complexity of f

hardwarearxiv-cs-cv

Local Ai

PartiCam: Camera Controlled Video Generation with Reward Guidance

arXiv:2609.39504v1 Announce Type: cross Abstract: We present PartiCam, a training-free Particle filtering rooted method for improved Camera controlled video generation. Generating videos that follow a

local-aiarxiv-cs-ai

PassGPT+: Leveraging Linguistic Priors for Password Modeling

arXiv:2609.39880v1 Announce Type: cross Abstract: Passwords remain the dominant online authentication mechanism, and understanding how humans choose them is essential for defensive strength estimation

Local Ai

Passive Stiffness Shaping in Cable-Suspended Aerial Manipulation via Movable Compliant Anchors

arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica

local-aiarxiv-cs-ro

PatchKV: Weight-Space Compensation of KV Cache

arXiv:2609.39329v1 Announce Type: new Abstract: Long-context inference with Large Language Models (LLMs) is bottlenecked by the linearly growing memory of the key-value (KV) cache. Existing compressio

Path-Following Control and Terramechanics Analysis for Planetary Rovers Under Wheel-to-Wheel Traction Asymmetry

arXiv:2609.38715v1 Announce Type: new Abstract: This paper proposes a control strategy for path following that is model-free and relies solely on deceleration for skid-steering planetary rovers naviga

researcharxiv-cs-ro

PathAnchor: Path-Structured Evidence for Scientific Agents

arXiv:2609.38766v1 Announce Type: new Abstract: Scientific agents can retrieve relevant passages yet still lose functional order, mix evidence across sources, or state conclusions that exceed the retr

agentsarxiv-cs-ai

Patient-Centered Treatment Planning for Chronic Multimorbidity: A Hierarchical Reinforcement Learning Framework for Preference Modeling

arXiv:2609.39911v1 Announce Type: new Abstract: Patient preference, defined as a patient's demonstrated willingness and capacity to adhere to clinical recommendations, is a primary determinant of ther

PCB-MC: Missing Component Analysis in Printed Circuit Boards

model-releasesarxiv-cs-cv

arXiv:2609.39427v1 Announce Type: new Abstract: Detecting missing components on printed circuit boards (PCBs) differs fundamentally from conventional object detection, as the model must localize compo

PEG-Tab: Sampling-Time Record Repair and Release Control for Tabular Synthesis

arXiv:2609.39630v1 Announce Type: new Abstract: Pretrained tabular generators can reproduce training records even when aggregate utility remains high. When retraining is unavailable or too costly, sam

Perceptual Color Difference Modeling Using Machine Learning and Human Similarity Judgments

arXiv:2609.39130v1 Announce Type: new Abstract: Accurate assessment of color differences is essential for applications ranging from digital design to quality control. While existing color difference m

Persistent Context Graphs for Efficient Memory Compaction in LLM Agents

arXiv:2609.40118v1 Announce Type: new Abstract: As LLM capabilities advance, agents are tackling increasingly complex tasks over longer horizons. Their growing interaction histories make memory compac

researcharxiv-cs-cl

Persistent Watermarking of Text-to-Image Models

arXiv:2609.39024v1 Announce Type: new Abstract: Text-to-image (T2I) generation is gaining increasing popularity with the general public, motivating the development of reliable mechanisms for copyright

Persona and Persuasive Framing in AI Voice Agents: A 2imes2 Field Experiment with Children

arXiv:2609.38782v1 Announce Type: new Abstract: Conversational agents increasingly interact with children, yet evidence on how their design shapes children's susceptibility to persuasion comes almost

agentsarxiv-cs-ai

Personalized State-Transition-Aware Memory for Clinical Agents

arXiv:2609.38490v1 Announce Type: cross Abstract: Large language model (LLM) agents that reason over clinical records must track changes in a patient's state while preserving the history needed to und

PhantomEnvironments: Training LLM Agents in Fictional Worlds

arXiv:2609.40221v1 Announce Type: cross Abstract: Training LLM agents with reinforcement learning (RL) is bottlenecked by environments, which must provide verifiable rewards, support long-horizon inte

PhasePlan: Ordered Future-Phase Planning for Robot Brain Models

arXiv:2609.39970v1 Announce Type: new Abstract: Robot brain models integrate vision, language, and robot state to generate actions for complex manipulation tasks. Most predict fixed-length action chun

safetyarxiv-cs-ro

PhaseSync-Exo: Human Clock Anchored Reference Adaptation for Dynamic Gait Tracking

arXiv:2609.38824v1 Announce Type: new Abstract: Human-aware exoskeleton walking requires reconstructing gait, tracking diverse motions under dynamic constraints, and preserving human timing. We presen

safetyarxiv-cs-ro

PhyProbe: Rethinking Physical Consistency Evaluation in Generated Videos

arXiv:2609.38377v1 Announce Type: new Abstract: Evaluating the physical consistency of generated videos remains a fundamental challenge. Existing approaches rely on off-the-shelf vision-language model

Physics-Informed Method of Group Data Handling: Adaptive Construction of Functional Representations with an Application to the Navier-Stokes Equations

arXiv:2609.39291v1 Announce Type: new Abstract: Physics-informed computational methods usually optimize parameters within a functional representation whose structure is fixed in advance. This work pro

Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model

arXiv:2609.40358v1 Announce Type: new Abstract: Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical

agentsarxiv-cs-cv

PINNing the pion: conformal deep learning for F_pi(s) and the (g-2)_mu hadronic contribution

arXiv:2609.40008v1 Announce Type: cross Abstract: Extracting the pion electromagnetic form factor F_{pi}(s) through phenomenological curve-fitting models introduces model dependence, unphysical artefa

PISCO: Precise Video Instance Insertion with Sparse Control

arXiv:2602.08277v3 Announce Type: replace-cross Abstract: The landscape of AI video generation is undergoing a pivotal shift: moving beyond general generation - which relies on exhaustive prompt-engin

PivotOPD: Learning to Recover from Pivotal Mistakes in Multi-Turn Agents

arXiv:2609.40285v1 Announce Type: new Abstract: On-policy distillation (OPD) is a promising approach for training language agents, providing dense teacher supervision on student-generated trajectories

PixelUMM: Encoder-Free Unified Image and Video Understanding and Generation

arXiv:2609.38597v1 Announce Type: new Abstract: Unified Multimodal Models (UMMs) often rely on separate visual representations for understanding and generation, increasing visual context length and co

Plan-Conditioned Imitation for Robust Object Retrieval under Self-Occlusion in Dense Clutter

model-releasesarxiv-cs-ro

arXiv:2609.38857v1 Announce Type: new Abstract: Retrieving objects from dense clutter requires rearrangement during which the manipulator can occlude objects while moving them. Repeated arm withdrawal

PLRS-IC: A Dual-Calibration Framework for Chest X-Ray Vision-Language Alignment

model-releasesarxiv-cs-cv

arXiv:2609.39266v1 Announce Type: new Abstract: Fine-grained vision-language alignment in chest radiography enables zero-shot classification, grounding, and segmentation without task-specific annotati

PMosFM: Preconditioned Manifold Matching for One-Step Physics-Constrained Generation

arXiv:2609.40287v1 Announce Type: new Abstract: Physics-constrained generative models aim to generate physical fields that match a target distribution and satisfy prescribed constraints. However, enfo

Applications

PneuTac: Tactile Manipulation with Soft Pneumatic Robots via Unified MPM-Gaussian Splatting Simulation

arXiv:2609.38418v1 Announce Type: new Abstract: Soft robots and tactile sensors have demonstrated great potential in delicate manipulation tasks. Soft pneumatic robots enable safe contact through comp

applicationsarxiv-cs-ro

Policy-Conditioned AI-Use Detection: An Evidentiary Framework for Academic Publishing

arXiv:2609.38427v1 Announce Type: cross Abstract: Major venues now publish detailed rules about how authors, reviewers, and area chairs may use AI, and those rules differ by role, by task, and by what

safetyarxiv-cs-ai

Policy Iteration Is Not Strongly Polynomial for Deterministic Markov Decision Processes: The Price of Algorithmic Anarchy

arXiv:2609.40147v1 Announce Type: new Abstract: We establish an exponential iteration lower bound in the number of states for Howard's policy iteration on deterministic discounted Markov decision proc

safetyarxiv-cs-lg

Positive Ratings, Hidden Concerns: Employee Voice Disclosure in AI-Mediated Organizational Listening

arXiv:2609.38788v1 Announce Type: new Abstract: Organizations started listening to employees through conversational AI agents alongside structured surveys. Little is known about what these channels ch