Search: “safety”

Aligning Network Equivariance with Data Symmetry: A Theoretical Framework and Adaptive Approach for Image Restoration

arXiv:2605.13744v1 Announce Type: new Abstract: Image restoration is an inherently ill posed inverse problem. Equivariant networks that embed geometric symmetry priors can mitigate this ill posedness

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AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation

DGX agent

arXiv:2605.13724v1 Announce Type: cross Abstract: Few-step video generation has been significantly advanced by consistency distillation. However, the performance of consistency-distilled models often

safetyarxiv-cs-ai

14 May 2026

Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions

arXiv:2602.02560v2 Announce Type: replace-cross Abstract: Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workl

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

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,

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

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

safetyarxiv-cs-ro

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

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

Model Releases

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

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

safetyarxiv-cs-ro

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

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

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

Improving Classifier-Free Guidance of Flow Matching via Manifold Projection

arXiv:2601.21892v2 Announce Type: replace-cross Abstract: Classifier-free guidance (CFG) is a widely used technique for controllable generation in diffusion and flow-based models. Despite its empirica

Improving Code Translation with Syntax-Guided and Semantic-aware Preference Optimization

arXiv:2605.13229v1 Announce Type: new Abstract: LLMs have shown immense potential for code translation, yet they often struggle to ensure both syntactic correctness and semantic consistency. While pre

Improving Diffusion Posterior Samplers with Lagged Temporal Corrections for Image Restoration

arXiv:2605.12573v1 Announce Type: cross Abstract: Diffusion-based posterior sampling (PS) is a leading framework for imaging inverse problems, combining learned priors with measurement constraints. Ye

In-Situ Behavioral Evaluation for LLM Fairness, Not Standardized-Test Scores

arXiv:2605.12530v1 Announce Type: cross Abstract: LLM fairness should be evaluated through in-situ conversational behavior rather than standardized-test Q&A benchmarks. We show that the standardized-t

interwhen: A Generalizable Framework for Steering Reasoning Models with Test-time Verification

arXiv:2602.11202v3 Announce Type: replace-cross Abstract: Reasoning models produce long traces of intermediate decisions and tool calls, making test-time verification important for ensuring correctnes

Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models

arXiv:2605.12725v1 Announce Type: new Abstract: Recent video anomaly detection research has expanded rapidly with an emphasis on general models of normality intended to work across many different scen

Model Releases

Learning Responsibility-Attributed Adversarial Scenarios for Testing Autonomous Vehicles

model-releasesarxiv-cs-ro

arXiv:2605.13751v1 Announce Type: new Abstract: Establishing trustworthy safety assurance for autonomous driving systems (ADSs) requires evidence that failures arise from avoidable system deficiencies