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PEARL: Process-Experience Aware Reinforcement Learning for Multi-Turn Agents

arXiv:2610.14636v1 Announce Type: new Abstract: Terminal rewards make multi-turn agents trainable without step-level annotations, but group-relative advantages provide little guidance about which inte

safetyarxiv-cs-ai

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Penumbra: Sample-Efficient Adversarial Search for Regulatory Obligations

DGX agent

arXiv:2610.04693v2 Announce Type: replace Abstract: Agents are entering finance, healthcare and law, sectors where a violation leaves no lexical signature and carries real penalties. Whether an omissi

agentsarxiv-cs-ai

15 Oct 2026

PersEvalBench: Can LLM Evaluators Judge Contextually Appropriate Use of Persona Information?

model-releasesarxiv-cs-cl

arXiv:2610.19314v1 Announce Type: new Abstract: Large language model (LLM) evaluators are increasingly used to assess personalized assistants, yet whether they can reliably judge personalization has r

PerSo: Investigating Facets of LLMs' Social Intelligence in Real-World Persuasion Scenarios

model-releasesarxiv-cs-cl

arXiv:2610.20548v1 Announce Type: new Abstract: Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and mult

Phantom Merge: When Your Large Language Model Agents Pick One but Tell You About Another

arXiv:2610.16141v1 Announce Type: new Abstract: LLM agents increasingly operate over multiple entities, where reliable response generation requires not only retrieving relevant evidence but also prese

PhyMetric: Diagnosing Physical Plausibility in Text-to-Video Generation via Scene-Level QA

model-releasesarxiv-cs-cv

arXiv:2610.19823v1 Announce Type: new Abstract: Text-to-video (T2V) generation models can produce visually realistic videos that nevertheless violate the physical consequences implied by the prompt an

PhysCodeGym: Benchmarking Coding Agents for Physically Verifiable 4D Reconstruction

arXiv:2610.17288v1 Announce Type: new Abstract: Building physical simulations from video requires coding agents to translate observations into executable models and refine them through tool use. We in

PhySGA: A Physics-Space Grounded Agentic Framework for Generalizable and Interactive 3D Composition

arXiv:2610.20560v1 Announce Type: cross Abstract: 3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence

safetyarxiv-cs-cv

Physical Layer Anomaly Detection via Adaptive Gaussian Mixture Model

model-releasesarxiv-cs-lg

arXiv:2610.18946v1 Announce Type: cross Abstract: Physical-layer spoofing attacks pose a critical threat to wireless localization systems by manipulating channel state information (CSI). Detecting suc

Physical Time as a Missing Dimension of Robot Policy Memory Dynamics

arXiv:2610.20524v1 Announce Type: new Abstract: Existing robot policy memories typically evolve with observation sequences, implicitly treating each update as the same amount of physical time. Yet ide

safetyarxiv-cs-ro

Physics: Benchmarking Foundation Models on University-Level Physics Problem Solving

arXiv:2503.21821v2 Announce Type: replace Abstract: We introduce Physics, a benchmark for evaluating foundation models on advanced physics problem solving. It contains 1034 annotated, open-ended probl

Physics-Guided Multi-Fidelity Surrogate Modeling for Natural Supercavity Geometry of an Axisymmetric Conical Cavitator

arXiv:2610.18886v1 Announce Type: cross Abstract: Natural supercavitation behind conical cavitators generates a vapor-filled envelope that, when sustained over the full body of a high-speed underwater

Physics-Shaped, Not Physical: Auditing Physics-Guided Underwater Image Restoration

arXiv:2610.19763v1 Announce Type: new Abstract: Physics-guided networks for underwater image restoration predict transmission and backscatter and invert the image-formation model, yet rarely test whet

safetyarxiv-cs-cv

pi-CoT: Prolog-Initialized Chain-of-Thought Prompting for Multi-Hop Question-Answering

arXiv:2506.20642v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting significantly enhances large language models' (LLMs) problem-solving capabilities, but still struggles with complex

researcharxiv-cs-cl

Applications

PingpongDuo: Agile Humanoid Table Tennis Doubles with Safe Team Coordination

arXiv:2610.20579v1 Announce Type: new Abstract: Unlike singles, humanoid table tennis doubles requires teammates to strike in strict alternation while sharing a confined workspace. Rapid repositioning

applicationsarxiv-cs-ro

PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation

model-releasesarxiv-cs-cl

arXiv:2603.23678v2 Announce Type: replace Abstract: Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy const

Plans Fade Fast: Why Context Management Is Load-Bearing for LLM Agents

arXiv:2606.22953v2 Announce Type: replace Abstract: Context managers summarize or evict old messages so agents can operate beyond a finite window. This creates a reliability problem: removing history

Plant Memory: Technical Language Processing and a Verified Maintenance Ontology for Agent-Accessible Failure Knowledge from SAP PM Work Orders

arXiv:2610.19131v1 Announce Type: cross Abstract: Maintenance work orders are the largest written record of how industrial equipment fails, yet in most plants they are close to unusable for analysis.

agentsarxiv-cs-cl

Player-1: Learning to Play from Synthetic Experience

arXiv:2610.20584v1 Announce Type: new Abstract: Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their v

agentsarxiv-cs-cv

PMO-Dock: Benchmarking Docking, Specificity, and Generalization in Molecular Optimization

model-releasesarxiv-cs-lg

arXiv:2610.19011v1 Announce Type: new Abstract: The Practical Molecular Optimization (PMO) benchmark standardized evaluation in molecular optimization, but it is built on simple property-based oracles

PN-Mix: Pair-Norm Guided Mixed-Precision Key Cache Quantization for Efficient Long-Output LLM Inference

arXiv:2610.19605v1 Announce Type: cross Abstract: Long-output inference in large language models suffers from severe KV cache memory and bandwidth bottlenecks. While KV cache quantization alleviates t

researcharxiv-cs-cl

Policy-Verified Self-Training: Learning Agent Compliance from Verifiable Policy Rewards

model-releasesarxiv-cs-lg

arXiv:2610.19372v1 Announce Type: new Abstract: Runtime policy verifiers can prevent agents from executing disallowed actions, but their decisions are typically used only for enforcement and discarded

Pollard: Governed Semantic Execution Trees for Framework-Independent AI Agent Control and Replay

arXiv:2610.16145v1 Announce Type: new Abstract: Agent frameworks can persist checkpoints, trace tool calls, and limit resource use, but these facilities often assign different identities to execution,

PolyMorph: Learning Locomotion Policy for Cross-Embodiment Adaptation

arXiv:2610.19615v1 Announce Type: new Abstract: Reinforcement learning has enabled robust locomotion for legged robots, but learned policies are typically tied to a specific robot morphology and requi

safetyarxiv-cs-ro

Polyrating: A Cost-Effective and Bias-Aware Rating System for LLM Evaluation

arXiv:2409.00696v4 Announce Type: replace-cross Abstract: Rating-based human evaluation has become an essential tool to accurately evaluate the impressive performance of large language models (LLMs).

PopGen: Generating Semantically Diverse Populations for Zero-Shot Coordination

arXiv:2610.15969v1 Announce Type: new Abstract: In multi-agent reinforcement learning, exposing a cooperator to partners with diverse strategies during training is key to better collaboration at test

safetyarxiv-cs-ai

Popularity Trajectories and Mixing Patterns of Urban Venues in Two European Cities

arXiv:2610.18917v1 Announce Type: cross Abstract: Urban venues such as restaurants, shops, bars and parks host the daily life of a city, and their collective rise and fall signals how vibrant a neighb

Post-Training, Finetuning, and Steering:A Field Guide for Curating Training Data

arXiv:2610.19143v1 Announce Type: new Abstract: While Vision-Language-Action models have enabled impressive cross-task transfer in zero-shot settings, adaptation methods are often necessary to achieve

safetyarxiv-cs-ro

Posterior Frequencies and the Cost of Not Fitting: A Correction to a Memorization Lower Bound

arXiv:2610.20402v1 Announce Type: cross Abstract: Feldman's memorization lower bound assigns a frequency coefficient based on how often a point appears in the training sample. We give an exact three-p

Pre-Registered Genesis Accounting for Recursive Self-Improvement: First Audited Operator-Genesis Events in a Physics-Discovery Runtime

arXiv:2610.14843v1 Announce Type: new Abstract: Claims of recursive self-improvement are easy to make and hard to falsify: did improvement come from re-using designer-provided mechanisms, or from mech

Pre-Trained Language Models as Zero-Shot Tools for Social Science Research

arXiv:2610.19048v1 Announce Type: new Abstract: Record linkage and demographic inference from names are routine demands in social science. Most approaches to these problems require labeled training da

safetyarxiv-cs-cl

PreciseCoder: Faithful and Generalizable Debugging Beyond Unit-Test Rewards

arXiv:2610.18755v1 Announce Type: cross Abstract: Reinforcement learning (RL) from unit tests is the common recipe for post-training code models, but a unit test only asks whether the final program pa

Predicting how model propensities generalize out of distribution

arXiv:2610.14937v1 Announce Type: new Abstract: How do language models generalize from their training data? This is a central challenge for alignment: models reliably learn their training distribution

Tutorials

Predicting Unseen Scientific Interactions: Conditional Flow Models Hallucinate Non-Additive Effects

arXiv:2610.20288v1 Announce Type: new Abstract: Conditional generative models are increasingly used for scientific prediction beyond the direct training support. Yet scientific questions often concern

tutorialsarxiv-cs-lg

Price of Anarchy of First-Price Auctions in Agentic Markets

arXiv:2610.20587v1 Announce Type: cross Abstract: An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt. An agent's bid is based on its expected value

agentsarxiv-cs-lg

PRIMEdit: Probability Redistribution for Instance-Aware Multi-Object Video Editing With a New Benchmark Dataset

model-releasesarxiv-cs-cv

arXiv:2412.12877v3 Announce Type: replace Abstract: Recent Artificial Intelligence (AI)-based video editing has enabled users to edit videos through simple text prompts, significantly simplifying the

PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis

arXiv:2610.20538v1 Announce Type: new Abstract: Multimodal code intelligence connects the symbolic world of programs with the visual world their execution creates. Interest in this capability is burge

researcharxiv-cs-cl

PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making

arXiv:2610.19762v1 Announce Type: new Abstract: Medical prescribing errors for multimorbid patients, who require complex drug regimens, are a major patient safety concern. These errors often stem from

safetyarxiv-cs-cl

PrivacyGuard: Source-Linked Sanitization and Locally Resolvable PII References for Cloud GUI Agents

arXiv:2610.16778v1 Announce Type: cross Abstract: Cloud graphical user interface (GUI) agents send instructions and screenshots to remote planners, exposing personally identifiable information (PII).

researcharxiv-cs-ai

Tutorials

Probabilistic Physics Digital Twin for Human-Robot Interaction

arXiv:2610.19336v1 Announce Type: new Abstract: Digital twins are increasingly used in robotics to simulate interactions, predict action outcomes, and support planning. However, constructing accurate

tutorialsarxiv-cs-ro

Probable but Not Valid: A Psychometric Audit of Decision Models as Synthetic Survey Respondents

arXiv:2610.14912v1 Announce Type: new Abstract: Language models are increasingly used to create synthetic survey samples, also called silicon samples. Decision models are a new class of language model

ProCARE: Real-World Study Automation via Profile-Grounded Evidence Contracts

arXiv:2610.16175v1 Announce Type: new Abstract: Real-world studies (RWS) analyze routinely collected healthcare data, such as electronic health records and insurance claims, to estimate treatment effe

ProgAgent: Learning Tool Orchestration through Programmatic Training

arXiv:2610.14774v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly expected to orchestrate diverse tools over long-horizon tasks. Existing agents typically use Direct Tool C

Progress-Aware Distillation for Mitigating Stagnation in Small Language Model Agents

arXiv:2610.19439v1 Announce Type: new Abstract: While LLM-based agent systems have demonstrated remarkable proficiency in reasoning and solving complex real-world tasks, they also come with substantia

agentsarxiv-cs-lg

Projected Wasserstein-Fisher-Rao Flows for Hawkes Background-Intensity Estimation

arXiv:2610.19588v1 Announce Type: cross Abstract: We consider the problem of estimating the background intensity of a Hawkes process when the triggering mechanism is known, treating the background as

Prompt Stability Matters: Evaluating and Optimizing Auto-Generated Prompt in General-Purpose Systems

arXiv:2505.13546v2 Announce Type: replace-cross Abstract: Automatic prompt generation plays a crucial role in enabling general-purpose multi-agent systems to perform diverse tasks autonomously. Existi

agentsarxiv-cs-cl

ProReviewer: Evidence-Driven Investigation for Scientific Peer Review

arXiv:2606.13349v2 Announce Type: replace Abstract: Effective peer review requires adaptive investigation that responds to evidence emerging from each paper. Existing LLM-based reviewers largely organ

agentsarxiv-cs-cl

PROSE: Training-Free Egocentric Scene Registration with Vision-Language Models

arXiv:2606.16569v2 Announce Type: replace Abstract: Registering two captures of the same indoor space taken at different times underpins persistent spatial memory for robots and AR systems, yet the re

researcharxiv-cs-cv