Search: “safety”

MorphoCLIP: Text-Supervised Contrastive Learning for Perturbation Matching in Cell Painting Images

arXiv:2608.22690v1 Announce Type: new Abstract: Cell Painting microscopy captures how cells change after a chemical or genetic perturbation. Connecting these images to the perturbations that produced

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MOSH-WM: Mask-Grounded Soft-Hamiltonian Dynamics for Object-Centric World Models

DGX agent

arXiv:2608.22750v1 Announce Type: new Abstract: Object-centric world models forecast future videos by evolving a set of entity slots, but the variables receiving dynamics supervision are often unconst

safetyarxiv-cs-lg

25 Aug 2026

Motion-Aware Vision-Reference Alignment for Referring Multi-Object Tracking

arXiv:2511.17681v2 Announce Type: replace Abstract: Referring Multi-Object Tracking (RMOT) extends conventional multi-object tracking (MOT) by introducing natural language references for multi-modal f

ODG-NoMaD: Overhead-Camera Direction-Guided NoMaD

arXiv:2608.21395v1 Announce Type: cross Abstract: NoMaD [31] is a learned vision-navigation policy that unifies goal-conditioned navigation and exploration in a single goal-masked diffusion policy. In

On the Capability Separation Between World-Model Policy Learning and Imitated World-Action Models

arXiv:2608.22197v1 Announce Type: new Abstract: World-action models predict a future outcome and then infer an associated action. Although this factorization can improve representation learning and da

On the Optimized Use of Non-Orthonormality Constraints for the Quasi-Static INS Alignment of Autonomous Underwater and Surface Vehicles

arXiv:2608.21390v1 Announce Type: new Abstract: Inertial navigation systems are specialized navigation apparatuses that equip almost all autonomous underwater and surface vehicles. They require precis

safetyarxiv-cs-ro

Optimal Transport for Handwritten Text Recognition in a Low-Resource Regime

arXiv:2509.16977v2 Announce Type: replace Abstract: Handwritten Text Recognition (HTR) is a task of central importance in the field of document image understanding. State-of-the-art methods for HTR re

Personalized and Aspiration-Oriented Career Path Recommendation

arXiv:2608.22056v1 Announce Type: new Abstract: Fulfilling career aspirations is important for growth of employee and organization. We propose a data driven methodology to recommend personalized caree

Perturb the Thought, Not the Pixels: Latent-Space Rollout Diversification for Reinforcement Learning of Vision-Language Models

arXiv:2608.21595v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning ability of vision-language models (VLMs), and diversifying the rollouts wit

Pointing-VLA: Typed Spatial Grounding Interfaces for Vision-Language-Action Manipulation

arXiv:2608.23138v1 Announce Type: cross Abstract: Vision-language-action (VLA) models often expose spatial grounding through autoregressive text coordinates or opaque action tokens, creating brittle i

Posterior Information Dynamics of Diffusion Models for Linear Inverse Problems

arXiv:2608.21709v1 Announce Type: new Abstract: Diffusion models are widely used as priors for linear inverse problems, yet endpoint quality does not reveal when measurement information enters reverse

Privileged Critic Training Enables Sensor-Free Thruster Fault Adaptation in End-to-End RL

arXiv:2608.22976v1 Announce Type: new Abstract: Fault-tolerant navigation for thruster-actuated robots requires online adaptation to failures that are neither binary nor fully observable: thrusters ma

safetyarxiv-cs-ro

Q-Learning with Stable Infinite-Dimensional Linear Function Approximation

arXiv:2608.22636v1 Announce Type: new Abstract: Q-learning with linear function approximation can be unstable because an arbitrary approximation architecture need not preserve the Bellman contraction.

QIRL: Optimized Question-Image Relation Learning for Bias-Robust Visual Question Answering

arXiv:2504.03337v2 Announce Type: replace Abstract: Existing bias mitigation methods for Visual Question Answering (VQA), a typical Artificial intelligence application, endure two main limitations. Fi

RAG Collapse: LLM Responses Collapse When Retrieved Documents Are Self-Authored

arXiv:2608.22118v1 Announce Type: new Abstract: LLM responses are based on the internet (via training or RAG), and AI is now used to generate a significant amount of content online (Paredes et al., 20

ReART: Reference-Guided Retrieval and Refinement for Emotion-Aware Art Generation

arXiv:2608.22329v1 Announce Type: cross Abstract: Emotion-aware artistic image generation requires a model to satisfy semantic content, artistic style, and target emotion simultaneously. The key chall

Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generation

arXiv:2505.17571v2 Announce Type: replace Abstract: Personalization is a critical task in modern intelligent systems, with applications spanning diverse domains, including interactions with large lang

Reinforcing the World's Edge: A Continual Learning Problem in the Multi-Agent-World Boundary

arXiv:2603.06813v2 Announce Type: replace Abstract: In a stationary decentralized Markov game, learning peers generate an episode-indexed sequence of induced MDPs for any focal agent. The joint game r

Reward-Free Continual Adaptation for Resilient Space Robots

arXiv:2608.23452v1 Announce Type: cross Abstract: Space robots operate in extreme environments where hardware degradation can critically compromise traditional control strategies. While continual rein

RIACT: A Responsible AI System for Personalized Study Habit Tracking and Early Burnout Signal Detection in University Students

arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin

Risk-Sensitive Reinforcement Learning with Smoothed Quantile Objectives

arXiv:2608.22227v1 Announce Type: new Abstract: Reinforcement Learning (RL) has achieved tremendous success in recent years. However, the classical foundations of RL do not account for the risk sensit

Robust Bimanual Vision-Language-Action Models via Embarrassingly Simple Modality Masking

arXiv:2608.22419v1 Announce Type: cross Abstract: Query-based Vision-Language-Action (VLA) models offer low-latency inference that is attractive for bimanual robotic manipulation, but we observe that

Robustness Analysis of Agentic AI to Inconsistent and Incomplete Tool Responses

arXiv:2608.22676v1 Announce Type: new Abstract: Robustness to a bad tool return means answering it in the way that return calls for, which depends on how the tool went wrong. A tool that has failed an

RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains

arXiv:2602.03002v2 Announce Type: replace Abstract: Humanoid perceptive locomotion has made significant progress and shows great promise, yet achieving robust multi-directional locomotion on complex t

safetyarxiv-cs-ro

Runtime Action Interference for AI Control of AlphaStar in StarCraft II

arXiv:2608.21398v1 Announce Type: cross Abstract: A trained reinforcement learning policy does not determine the complete behavior that users encounter: deployment code still schedules, admits, suppre

Scaling Curriculum Learning For Autonomous Driving

arXiv:2608.22549v1 Announce Type: new Abstract: Batched simulators for autonomous driving have recently enabled training reinforcement learning (RL) agents at scale, encompassing thousands of traffic

SCAR: Semantic Continuity-Aware Retrieval for Efficient Context Expansion in RAG

arXiv:2606.16661v2 Announce Type: replace-cross Abstract: Fixed-length chunking in Retrieval-Augmented Generation (RAG) often leads to boundary fragmentation, where critical evidence is split across s

SDoH-Aware Narrative Anchoring Bias in Medical LLMs for Trustworthy Clinical Decision Support

arXiv:2608.22802v1 Announce Type: cross Abstract: Medical large language models are often judged by how many clinical questions they answer correctly. That view is useful, but it misses a practical ri

SecOPD: Mitigating Adaptive Prompt Injections by On-Policy Distillation

arXiv:2608.21500v1 Announce Type: cross Abstract: Prompt injection is listed as the #1 threat to AI agents. When an agent accesses external data from websites, files, or emails, an attacker may inject

Self-Supervised Graph Representation Learning for In-The-Wild Wearable and Smartphone based Emotion Recognition

arXiv:2608.22387v1 Announce Type: cross Abstract: Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias

Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference

arXiv:2501.06926v5 Announce Type: replace-cross Abstract: Double reinforcement learning (DRL) provides efficient off-policy inference for policy values in nonparametric Markov decision processes (MDPs

Shaping the Evolutionary Dynamics of Robot Morphology via Adaptive Control Learning

arXiv:2608.23100v1 Announce Type: cross Abstract: Robot co-design via bi-level optimization couples within-lifetime controller learning for fitness evaluation with cross-generational morphological evo

Simplified Cross-Modal Calibration for Heterogeneous Event-RGB Stereo Systems

arXiv:2608.22965v1 Announce Type: new Abstract: Accurate extrinsic calibration between event-based and frame-based cameras remains a practical bottleneck for heterogeneous stereo systems. Existing app

SketchFlow: Zero-Shot Vector Sketch Generation via GMM Prior Flow in CLIP Latent Space

arXiv:2608.21659v1 Announce Type: new Abstract: Vector sketches remain one of the most concise and immediate mediums for abstract human expression. However, generating high-quality vector strokes that

Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories

arXiv:2608.22595v1 Announce Type: cross Abstract: We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle lar

SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning

arXiv:2608.23493v1 Announce Type: new Abstract: Self-reflection is a powerful mechanism for credit assignment in human learning, converting sparse outcome feedback into actionable guidance. However, i

SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning

arXiv:2608.22132v1 Announce Type: cross Abstract: Biomedical multi-hop question answering (QA) requires models to connect evidence across intermediate entities such as diseases, drugs, proteins, and p

STA-VPT: SpatioTemporally Aligned Visual Prompt Tuning

arXiv:2312.10376v2 Announce Type: replace Abstract: Typical methods for visual prompt tuning follow the sequential modeling paradigm originating from NLP, learning a sequence of unordered parameterize

SVD-Based Typicality Maps for Out-of-Distribution Detection in Vision Transformers

arXiv:2608.23499v1 Announce Type: new Abstract: We present a method for analyzing the internal representations of Vision Transformers (ViTs) exploiting the geometry of their learned parameters. Each a

Syntax-Guided Diffusion Language Models with User-Integrated Personalization

arXiv:2510.01028v2 Announce Type: replace Abstract: Large language models have made revolutionary progress in generating human-like text, yet their outputs often tend to be generic, exhibiting insuffi

TailSieve: Partial-Rollout-Guided Tail Routing for LLM Rollouts

arXiv:2608.22788v1 Announce Type: new Abstract: Large-scale rollouts have become a core component of modern LLM systems, spanning reinforcement learning (RL) post-training, on-policy distillation (OPD

The Plan, Not the Decoder: Diagnosing and Repairing Compositional Failure in Reasoning-Augmented Text-to-Image Generation

arXiv:2608.21713v1 Announce Type: cross Abstract: Reasoning-augmented text-to-image models such as GoT-R1 emit an explicit textual plan - object names, attributes, and bounding boxes - before generati

The Variance of Thought: Policy Variance, Critical Forks, and Local Credit Assignment

arXiv:2608.22467v1 Announce Type: new Abstract: Long-horizon language-model tasks --- multi-step reasoning and tool-using agents alike --- are limited by credit assignment. We analyze it through the p

Think Only When Needed: Prompt-Authority Control for Selective Slow-Path Intervention in Vision-Language-Action Manipulation

arXiv:2608.23224v1 Announce Type: cross Abstract: Retrieval can efficiently and effectively augment a frozen vision--language--action (VLA) policy without retraining, yet retrieved text becomes a cont

Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs

arXiv:2608.22854v1 Announce Type: new Abstract: Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style mod

Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning

arXiv:2608.21898v1 Announce Type: new Abstract: Web agents promise to automate complex digital workflows, but their training remains limited by synthetic environments that look plausible while hiding

UniMem: Unifying Multimodal Memory and Control for Vision-Language-Action Models

arXiv:2608.22869v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have leveraged internet-scale pretraining and task-focused finetuning to achieve strong performance on long-

Variance Driven Exploration: A Provable and Efficient Methodology for Pure Exploration in Highly Stochastic Environments

arXiv:2608.21995v1 Announce Type: cross Abstract: We propose Variance Driven Exploration (VarDE), a principled approach for pure exploration in highly stochastic environments, where the exploration pr