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High-Probability Nash Regret for Decentralized Learning in Markov alpha-Potential Games: Episodic and Fully Online Asynchronous Algorithms with Applications to Markov Congestion Games

arXiv:2609.14959v1 Announce Type: new Abstract: We study decentralized learning of Nash equilibria (NE) in infinite-horizon discounted Markov games under bandit feedback, focusing on Markov alpha-pote

safetyarxiv-cs-lg

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Hindsight-Anchored Policy Optimization: Learning Through Hindsight with Thompson Sampling-Inspired Adaptive Gating

arXiv:2603.11321v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards improves reasoning in large language models, yet on-policy learning often suffers from cold-sta

Hindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment

model-releasesarxiv-cs-ai

arXiv:2609.13454v1 Announce Type: cross Abstract: Clinical decisions are prospective, but clinical language models are often evaluated on retrospective records that reveal the final diagnosis, treatme

HISPO: Hierarchical Importance-Sampling Policy Optimization with Entropy-Derived Segments

arXiv:2609.15471v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a central approach for improving mathematical reasoning in language models, but long-fo

Homeostatic Continual Learning

arXiv:2609.13771v1 Announce Type: new Abstract: In this paper, I formulate a Continual Learning problem and propose a method named 'Homeostatic Continual Learning' that enables an AI agent to learn co

Horizon-specific Expert Fusion for Photovoltaic Power Forecasting

arXiv:2609.15035v1 Announce Type: new Abstract: Short-term photovoltaic power forecasting requires models to represent regular solar cycles and weather-driven fluctuations whose importance changes wit

How broad is that claim? Mapping Generalisation in NLP Research

arXiv:2609.14770v1 Announce Type: cross Abstract: Generalisations are common in scientific communication, even though they are semantically ambiguous. An automated method is needed to identify and cat

How Contrastive Decoding Enhances Large Audio Language Models

arXiv:2603.09232v2 Announce Type: replace-cross Abstract: While Contrastive Decoding (CD) has been proposed to enhance Large Audio Language Models (LALMs), it has not been evaluated at scale, and the

(How) Do MLLMs Report Bistable Images Like Humans?

arXiv:2609.13254v1 Announce Type: cross Abstract: Bistable images such as the duck-rabbit are classic stimuli in which one image supports multiple mutually incompatible interpretations, typically repo

How Lossless Is Lossless Speculative Decoding? The Role of Numerical Precision in Orthrus

arXiv:2609.15504v1 Announce Type: cross Abstract: Orthrus is a hybrid autoregressive-diffusion architecture that accelerates autoregressive language-model inference by generating multiple tokens in pa

How Many Thoughts Can a Vector Hold? The Capacity of Reasoning by Superposition

arXiv:2609.13747v1 Announce Type: new Abstract: Large language models solve hard problems through intermediate computations across multi-step reasoning. Traditional chain-of-thought encodes these comp

Local Ai

How Semantically Stable Are LLM Refusals? Measuring Confusion in Local Safety Boundaries

arXiv:2512.01037v3 Announce Type: replace-cross Abstract: As safety alignment becomes standard in large language models, refusal behavior has become an important part of model reliability. However, mo

local-aiarxiv-cs-ai

Tutorials

How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026

arXiv:2609.13679v1 Announce Type: new Abstract: How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 20

tutorialsarxiv-cs-ro

How User-AI Mistreatment Occurs and Matters in Conversational Systems?

arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding

How Well Do Pseudo-Rigid Body Models Capture Real Plants? In-Field Validation of Simulated Blueberry Canes

arXiv:2609.13627v1 Announce Type: new Abstract: Many labor-intensive tasks in fruit production such as pruning require physically interacting with the plant (e.g., pushing, pulling, bending limbs, etc

applicationsarxiv-cs-ro

HQARRF: Hierarchical Q-learning and Force-aware Routing for Multi-Charger Scheduling in Wireless Rechargeable Sensor Networks

model-releasesarxiv-cs-lg

arXiv:2609.13901v1 Announce Type: cross Abstract: Multi-charger scheduling in wireless rechargeable sensor networks must weigh sensor death risk, charger energy, travel cost, return-to-base feasibilit

Human-Grounded Calibration for Long-Text Image-Text Congruence in Vision-Language Models

arXiv:2609.15640v1 Announce Type: cross Abstract: Long-text image--text congruence scoring is increasingly important for vision-language systems that must evaluate whether detailed textual description

Local Ai

Human Pose-Constrained UV Map Estimation

arXiv:2501.08815v2 Announce Type: replace Abstract: UV map estimation is used in computer vision for detailed analysis of human posture or activity. Previous methods assign pixels to body model vertic

local-aiarxiv-cs-cv

Hardware

Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum

arXiv:2601.14172v4 Announce Type: replace-cross Abstract: We study neural multi-label classification under severe label imbalance through sentence-level detection of the 19 refined Schwartz human valu

hardwarearxiv-cs-ai

Hybrid Feedback-Guided Optimal Learning for Wireless Interactive Panoramic Scene Delivery

arXiv:2602.07273v2 Announce Type: replace Abstract: Immersive applications such as virtual and augmented reality impose stringent requirements on frame rate, latency, and synchronization between physi

applicationsarxiv-cs-lg

Agents

HydroMap: Probabilistic Water Surface Elevation Mapping for Semantic Scene Representation in Inland Waterways

arXiv:2609.14903v1 Announce Type: new Abstract: Autonomous surface vehicles operating in inland waterways require a persistent representation of both surrounding structures and the water surface. LiDA

agentsarxiv-cs-ro

Hyper-LLaVA: Hyperbolic Uncertainty-aware Modality-Balanced Routing for Multimodal Continual Instruction Tuning

model-releasesarxiv-cs-cv

arXiv:2609.13742v1 Announce Type: new Abstract: Multimodal Continual Instruction Tuning (MCIT) aims to exploit the incrementally accumulated knowledge to process multimodal inputs of diverse tasks, wh

Hypergraph-Regularized Gramian Volumes for Multimodal Retrieval

arXiv:2609.15320v1 Announce Type: new Abstract: Volume-based multimodal retrieval jointly scores a text query with a candidate's video, audio, and subtitle embeddings. While this approach captures hig

safetyarxiv-cs-cv

HyperProve: Answer-Guided Hypergraph Expansion for Multi-Hop Question Answering

arXiv:2609.13768v1 Announce Type: new Abstract: Multi-hop question answering often fails when retrieval treats evidence as isolated matches to the original question, since the facts needed to answer a

safetyarxiv-cs-cl

Hyperspectral Image Restoration and Super-resolution with Physics-Aware Deep Learning for Biomedical Applications

arXiv:2503.02908v2 Announce Type: replace-cross Abstract: Hyperspectral imaging is a powerful bioimaging tool which can uncover novel insights, thanks to its sensitivity to the intrinsic properties of

researcharxiv-cs-cv

Agents

HypoEvolve: Genetic Algorithms Enable Multi-Agent LLMs to Discover Scientific Hypotheses

arXiv:2609.15938v1 Announce Type: new Abstract: Scientific agents contribute to hypothesis discovery by synthesizing evidence, assessing proposals, and developing new explanations. Recent systems comb

agentsarxiv-cs-cl

IBBench-Light: A Paired Evaluation of Task-Conditioned Responses to External Directives

model-releasesarxiv-cs-ai

arXiv:2609.13725v1 Announce Type: new Abstract: An external record may contain a procedure to apply or text to read, depending on the user's request. IBBench-Light tests both uses against the same rec

Identifying and Transferring Reasoning-Critical Neurons: Improving LLM Inference Reliability via Activation Steering

arXiv:2601.19847v3 Announce Type: replace Abstract: Despite the strong reasoning capabilities of recent large language models (LLMs), achieving reliable performance on challenging tasks often requires

Identity Is More Than Recall: A Benchmark for Persistent Identity in Deployed AI Agents

model-releasesarxiv-cs-ai

arXiv:2609.13637v1 Announce Type: new Abstract: Persistent agents need evaluations that distinguish identity facts they can recall from those they express and enact. We introduce PAI-Bench, a provider

Agents

IMM-based Multiple Object Tracking using a State Prediction Neural Network

arXiv:2609.13307v1 Announce Type: cross Abstract: Object tracking is essential for autonomous vehicles to avoid obstacles and plan routes. Radar maintains detection performance even in adverse weather

agentsarxiv-cs-ai

IMPACT-VLA: Interaction-aware Multimodal Propagation Attribution via Counterfactual Trajectories for Vision-Language-Action Policies

arXiv:2609.15005v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies perform robot manipulation tasks using multimodal inputs such as visual observations, proprioceptive states, and

Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification

arXiv:2609.15145v1 Announce Type: new Abstract: The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning ca

Improving the Last-Iterate Guarantees of Anytime Algorithms for Stochastic Monotone Variational Inequalities

arXiv:2609.15257v1 Announce Type: cross Abstract: We analyze a stochastic algorithm with Halpern anchoring for constrained convex-concave problems and monotone variational inequalities. This algorithm

researcharxiv-cs-lg

Impute-EM: Native Mixed-State Diffusion Models for Heterogeneous Data Imputation

arXiv:2609.15284v1 Announce Type: new Abstract: Missing values are ubiquitous in heterogeneous data mining, where numerical, categorical, and binary variables often coexist. Many imputation methods, e

researcharxiv-cs-lg

In the Blind: Building Pseudo-References for MT Evaluation

arXiv:2609.13611v1 Announce Type: new Abstract: The WMT26 General MT task evaluates systems on 10 language pairs that have no human references (neither translated from scratch nor post-edited from MT

Inherited Heads: Audio language models track speakers with their text backbone's attention, and an attention-mass ranking retrieves a different set

arXiv:2609.14174v1 Announce Type: cross Abstract: Asked to describe what one of six speakers in a recording talks about, audio language models describe the right one on 6 to 16% of trials, below the 1

Inoculation Midtraining with Learned Neologisms

arXiv:2609.15886v1 Announce Type: new Abstract: Large language models (LLMs) often learn both desirable and undesirable properties during post-training. We study whether midtraining, an earlier traini

safetyarxiv-cs-cl

Inside VLM Chart Reading: Tracing Value Reading from Vertical Bar Charts Across Space and Depth

arXiv:2609.13745v1 Announce Type: new Abstract: Vision--language models (VLMs) can answer chart questions accurately, but output accuracy does not show how they combine the evidence needed to recover

Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows

arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi

researcharxiv-cs-cv

Inter-Rater Reliability of LLM and Rule-Based Annotation for Inferential Narrative Features: Three Studies on a Turkish Corpus

arXiv:2609.13936v1 Announce Type: new Abstract: Datasets that ship automatically generated feature annotations invite a question rarely asked of them: would a human agree with those labels? This repor

Interpolation Is Not Invariance: Pair Count Is Not Coverage in Transformation Audits

arXiv:2609.14870v1 Announce Type: cross Abstract: Counting equivalent pairs is a common way to report transformation-audit coverage, but it can substantially overstate the constraints imposed by an au

Interpretable Temporal Video Reasoning with EventGraph and EventField

arXiv:2609.13258v1 Announce Type: cross Abstract: We present a structured temporal video reasoning pipeline built around a discrete EventGraph, a continuous EventField, and a human-readable EventGlyph

Tutorials

Interpreting hierarchical organisation of speaker embeddings

arXiv:2609.15203v1 Announce Type: cross Abstract: Speaker recognition neural networks learn latent representations (i.e. speaker embeddings) from input utterances to recognise speaker identities. Howe

tutorialsarxiv-cs-ai

InterSocialBench: Benchmarking Human and LLM Preferences for Companion-Robot Social Behavior

model-releasesarxiv-cs-ro

arXiv:2609.15455v1 Announce Type: new Abstract: Companion robots face everyday situations in which several feasible behaviors may be appropriate, yet different people prefer different responses. We in

IntraGuard: Committee-Side Defenses Against Review Outsourcing to Commercial Chatbots

arXiv:2605.05271v2 Announce Type: replace-cross Abstract: LLMs become increasingly capable, editorial boards and program committees are growing concerned about reviewers who fully outsource peer revie

applicationsarxiv-cs-ai

Introspective Uncertainty Estimation for LLM-Based Code Generation

arXiv:2609.13975v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation but can produce fluent yet functionally incorrect outputs, which limits trust i

applicationsarxiv-cs-lg

Inverse Learning of the Altruism and Cost Level in Mixed-Individual Mean Field Games

model-releasesarxiv-cs-lg

arXiv:2609.13469v1 Announce Type: cross Abstract: Understanding how humans respond to incentives, both at the individual and collective levels, is crucial to the design of effective policies. Within t

Investigating the Impacts of Generative AI on Information Seeking

arXiv:2609.14638v1 Announce Type: cross Abstract: This paper is an encore submission of our 2026 journal article 'Expertise and Information Seeking in the Age of Generative AI: New Procedures, New Pro