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BEHAVE: A Hybrid AI Framework for Real-Time Modeling of Collective Human Dynamics

arXiv:2605.12730v1 Announce Type: new Abstract: Existing AI systems for modeling human behavior operate at the level of individuals or detect events after they occur. As a result, they systematically

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Belief-Space Residual Risk for Automated Driving under Localization Uncertainty

DGX agent

arXiv:2605.12710v1 Announce Type: new Abstract: Residual risk metrics have recently been introduced to assess the safety implications of automated driving systems. Existing approaches typically assume

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14 May 2026

Beyond Anthropomorphism: Exploring the Roles of Perceived Non-humanity and Structural Similarity in Deep Self-Disclosure Toward Generative AI

arXiv:2605.13574v1 Announce Type: cross Abstract: This study investigates deep self-disclosure toward generative AI by examining perceived non-humanity and structural similarity as psychological facto

Beyond VMAF: Towards Application-Specific Metrics for Teleoperation Video

arXiv:2605.13525v1 Announce Type: cross Abstract: Automated driving has made remarkable progress, yet situations still arise where human intervention is necessary. Teleoperation provides a scalable so

BlitzGS: City-Scale Gaussian Splatting at Lightning Speed

arXiv:2605.13794v1 Announce Type: cross Abstract: We present BlitzGS, a distributed 3DGS framework that reduces active Gaussian workload for fast city-scale reconstruction. BlitzGS manages this worklo

Block-wise Adaptive Caching for Accelerating Diffusion Policy

arXiv:2506.13456v2 Announce Type: replace Abstract: Diffusion Policy has demonstrated strong visuomotor modeling capabilities, but its high computational cost renders it impractical for real-time robo

Bridging Domain Gaps with Target-Aligned Generation for Offline Reinforcement Learning

arXiv:2605.13054v1 Announce Type: cross Abstract: Cross-domain offline reinforcement learning aims to adapt a policy from a source domain to a target domain using only pre-collected datasets, where en

CA-GCL: Cross-Anatomy Global-Local Contrastive Learning for Robust 3D Medical Image Understanding

arXiv:2605.13544v1 Announce Type: new Abstract: Fine-grained Vision-Language Pre-training (FVLP) demonstrates significant potential in 3D medical image understanding by aligning anatomy-level visual r

Causal Fine-Tuning under Latent Confounded Shift

arXiv:2410.14375v3 Announce Type: replace Abstract: Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlati

Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling

arXiv:2605.13646v1 Announce Type: cross Abstract: End-to-end autonomous driving, which bypasses traditional modular pipelines by directly predicting future trajectories from sensor inputs, has recentl

Centralized Adaptive Sampling for Reliable Co-Training of Independent Multi-Agent Policies

arXiv:2508.01049v2 Announce Type: replace Abstract: Independent on-policy policy gradient algorithms are widely used for multi-agent reinforcement learning (MARL) in cooperative and no-conflict games,

Certified Robustness under Heterogeneous Perturbations via Hybrid Randomized Smoothing

arXiv:2605.12876v1 Announce Type: new Abstract: Randomized smoothing provides strong, model-agnostic robustness certificates, but existing guarantees are limited to single modalities, treating continu

Characterizing Universal Object Representations Across Vision Models

arXiv:2605.13675v1 Announce Type: new Abstract: Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. Ho

ChatSR: Multimodal Large Language Models for Scientific Formula Discovery

arXiv:2406.05410v3 Announce Type: replace Abstract: Current multimodal large language models (MLLMs) are mainly focused on the understanding and processing of perceptual modalities such as images and

CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem

arXiv:2605.13638v1 Announce Type: cross Abstract: A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum c

Constraints-of-Thought: A Framework for Constrained Reasoning in Language-Model-Guided Search

arXiv:2510.08992v3 Announce Type: replace Abstract: While researchers have made significant progress in enabling large language models (LLMs) to perform multi-step planning, LLMs struggle to ensure th

Context Matters: Auditing Gender Bias in T2I Generation through Risk-Tiered Use-Case Profiles

arXiv:2605.13113v1 Announce Type: cross Abstract: Text-to-image (T2I) generative models are increasingly used to produce content for education, media, and public-facing communication, and are starting

Control where your AI agents can browse with Chrome enterprise policies on Amazon Bedrock AgentCore

In this post, you will configure Chrome enterprise policies to restrict a browser agent to a specific website, observe the policy enforcement through session recording, and demonstrate custom root CA

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COSMIC: Concurrent Optimization of Structure, Material, and Integrated Control for robotic systems

arXiv:2605.12654v1 Announce Type: new Abstract: Replicating and surpassing the autonomy of natural organisms remains a long-standing goal in robotics. Yet most robotic systems have their structure, ma

Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems

arXiv:2605.13077v1 Announce Type: cross Abstract: Responsibility allocation -- determining the extent to which agents are accountable for outcomes -- is a fundamental challenge in the design and analy

CRAFT: Clinical Reward-Aligned Finetuning for Medical Image Synthesis

arXiv:2605.12650v1 Announce Type: new Abstract: Foundation diffusion models can generate photorealistic natural images, but adapting them to medical imaging remains challenging. In medical adaptation,

CROP: Expert-Aligned Image Cropping via Compositional Reasoning and Optimizing Preference

arXiv:2605.12545v1 Announce Type: cross Abstract: Aesthetic image cropping aims to enhance the aesthetic quality of an image by improving its composition through spatial cropping. Previous methods oft

Data Agent: Learning to Select Data via End-to-End Dynamic Optimization

arXiv:2603.07433v2 Announce Type: replace-cross Abstract: Dynamic Data selection aims to accelerate training by prioritizing informative samples during online training. However, existing methods typic

Decision Support for Marketplace Policies under Incomplete Evidence: From Replay to Launch Readiness

arXiv:2605.12840v1 Announce Type: cross Abstract: Marketplace platforms routinely evaluate pricing and allocation policies using logged observational data, yet strong offline performance does not impl

Decoupling Exploration and Policy Optimization: Uncertainty Guided Tree Search for Hard Exploration

arXiv:2603.22273v4 Announce Type: replace Abstract: The process of discovery requires active exploration -- the act of collecting new and informative data. However, efficient autonomous exploration re

Delightful Distributed Policy Gradient

arXiv:2603.20521v2 Announce Type: replace-cross Abstract: Distributed reinforcement learning trains on data from stale, buggy, or mismatched actors, producing actions with high surprisal (negative log

Differentiable Evolutionary Reinforcement Learning

arXiv:2512.13399v2 Announce Type: replace Abstract: Crafting effective reward signals remains a central challenge in Reinforcement Learning (RL), especially for complex reasoning tasks. Existing autom

Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold

arXiv:2602.06021v2 Announce Type: replace-cross Abstract: We study a data-dependent notion of diffusion-model generalization: when a model does not memorize the training set, where do its generated sa

DiffusionHijack: Supply-Chain PRNG Backdoor Attack on Diffusion Models and Quantum Random Number Defense

arXiv:2605.13115v1 Announce Type: cross Abstract: Diffusion models depend on pseudo-random number generators (PRNGs) for latent noise sampling. We present DiffusionHijack, a supply-chain backdoor atta

Digital Twins as Synthetic Controls in Single-Arm Trials

arXiv:2605.12832v1 Announce Type: cross Abstract: Single-arm trials are an important study design for evaluating drug efficacy and safety without enrolling patients into a control arm. Although they d

DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models

arXiv:2605.12702v1 Announce Type: new Abstract: General-purpose safety benchmarks for large language models do not adequately evaluate disability-related harms. We introduce DisaBench: a taxonomy of t

Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach

arXiv:2605.12974v1 Announce Type: new Abstract: In this work, we study how to ensure probabilistic safety for nonlinear systems under distributional ambiguity. Our approach builds on a backup-based sa

Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions

arXiv:2605.12701v1 Announce Type: cross Abstract: Machine learning algorithms in socially sensitive domains (e.g., credit decisions) often focus on equalizing predictive outcomes. However, satisfying

DP-Muon: Differentially Private Optimization via Matrix-Orthogonalized Momentum

arXiv:2605.12994v1 Announce Type: new Abstract: We study differentially private (DP) training with Muon, a matrix-valued optimizer that updates hidden-layer weights using momentum followed by Newton--

Driving Intents Amplify Planning-Oriented Reinforcement Learning

arXiv:2605.12625v1 Announce Type: cross Abstract: Continuous-action policies trained on a single demonstrated trajectory per scene suffer from mode collapse: samples cluster around the demonstrated ma

Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer

arXiv:2605.12798v1 Announce Type: cross Abstract: Fine-tuning LLMs on narrow harmful datasets can induce Emergent Misalignment (EM), where models exhibit misaligned behavior far beyond the fine-tuning

Ergodic Trajectory Design by Learned Pushforward Maps: Provable Coverage via Conditional Flow Matching

arXiv:2605.13063v1 Announce Type: new Abstract: Designing continuous trajectories whose time-averaged occupancy provably matches a prescribed spatial density (the ergodic coverage problem) is central

ERPPO: Entropy Regularization-based Proximal Policy Optimization

arXiv:2605.13131v1 Announce Type: new Abstract: Multi-Agent Proximal Policy Optimization (MAPPO) is a variant of the Proximal Policy Optimization (PPO) algorithm, specifically tailored for multi-agent

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking

arXiv:2605.12995v1 Announce Type: new Abstract: Traditional retrieval pipelines optimize utility through stages of candidate retrieval and reranking, where ranking operates over a predefined candidate

Flow Matching for Offline Reinforcement Learning with Discrete Actions

arXiv:2602.06138v2 Announce Type: replace Abstract: Generative policies based on diffusion models and flow matching have shown strong promise for offline reinforcement learning (RL), but their applica

FrameSkip: Learning from Fewer but More Informative Frames in VLA Training

arXiv:2605.13757v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly trained from dense robot demonstration trajectories, often collected through teleoperation, by sampli

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation

arXiv:2605.12997v1 Announce Type: new Abstract: Neural operators learn to map initial conditions to the terminal solution of partial differential equations (PDEs), providing a surrogate for the full o

GAGPO: Generalized Advantage Grouped Policy Optimization

arXiv:2605.13217v1 Announce Type: cross Abstract: Reinforcement learning has become a powerful paradigm for post-training large language model agents, yet credit assignment in multi-turn environments

Generative Texture Diversification of 3D Pedestrians for Robust Autonomous Driving Perception

arXiv:2605.13755v1 Announce Type: new Abstract: In recent years, autonomous driving has significantly in creased the demand for high-quality data to train 2D and 3D perception models for safety-critic

GRACE: Gradient-aligned Reasoning Data Curation for Efficient Post-training

arXiv:2605.13130v1 Announce Type: new Abstract: Existing reasoning data curation pipelines score whole samples, treating every intermediate step as equally valuable. In reality, steps within a trace c

Graph-Based Financial Fraud Detection with Calibrated Risk Scoring and Structural Regularization

arXiv:2605.12782v1 Announce Type: new Abstract: Financial transaction fraud prevention faces challenges such as complex relationship structures, concealed behavioral patterns, and dynamically changing

Helping ChatGPT better recognize context in sensitive conversations

OpenAI implemented improvements to help ChatGPT better understand and respond appropriately to context in sensitive conversations, such as those involving mental health, abuse, or other delicate topic

safetyopenai

HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation

arXiv:2605.13581v1 Announce Type: new Abstract: Hyperspectral image (HSI) restoration is crucial for reliable analysis, as real HSIs suffer from degradations like noise, blur, and resolution loss. How