Search: “safety”

RL Bootstrapping of OpenVLA-OFT for a Novel Robot Embodiment

arXiv:2608.01013v1 Announce Type: new Abstract: Adapting a pretrained vision-language-action (VLA) policy to a new robot usually assumes embodiment-specific demonstrations. This assumption is especial

RMSWeb: Reflection, Failure-Mode Mining, and Salvage-DS for Web Agent Reinforcement Learning

DGX agent

arXiv:2608.00335v1 Announce Type: cross Abstract: Compact web agents can reduce deployment cost, but training them poses challenges in both data collection and post-SFT reinforcement learning (RL). Su

safetyarxiv-cs-cl

4 Aug 2026

RobotDancing: Residual-Action Reinforcement Learning Enables Robust Long-Horizon Humanoid Motion Tracking

arXiv:2509.20717v2 Announce Type: replace Abstract: Long-horizon, high-dynamic motion tracking on humanoids remains brittle: retargeted reference motions are typically kinematically plausible but dyna

Romanized Arabic Across Dialects: Views, Usage Patterns, and Linguistic Variation

arXiv:2608.02555v1 Announce Type: new Abstract: Arabizi refers to Arabic written in Latin script. Although previous studies have shown that the prevalence and usage of Arabizi vary by factors such as

Same Semantics, Different Paths: Self-Improving Alignment for Vision-Text Compression

arXiv:2608.02109v1 Announce Type: new Abstract: Vision-Text Compression (VTC) renders long texts into images and encodes them through the vision encoder (ViT), compressing thousands of text tokens int

Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics

arXiv:2608.01423v1 Announce Type: cross Abstract: Reference-based text evaluation metrics, which are widely used to assess natural language generation systems, score a candidate response by comparing

Self-Certification of Representation Adequacy: Sequential Certification at Minimum Task Loss

arXiv:2608.02267v1 Announce Type: cross Abstract: Agents that act on a compressed representation of their history face a structural risk: if the representation aliases histories with different optimal

SelfWAM: A Self-Grounded Unified World Action Model for Fast Robot Control

arXiv:2608.00725v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future observations. However, conditioning future prediction on

Semantic Alignment of AI Models: Concept Collapse, Checkpoint Dynamics, and Cross-Lingual Transfer

arXiv:2608.01585v1 Announce Type: new Abstract: Language model benchmarking is a difficult task. Outcome reasoning alone does not test the model's conceptualization of language and popular open-source

Semantically Calibrated Evidence Composition for CT Vision-Language Learning

arXiv:2608.00239v1 Announce Type: new Abstract: Learning transferable representations from CT-report pairs requires combining whole-volume context with anatomy-specific evidence. Existing methods typi

Sen-Cap: Sensor-Flexible and Noise-Resilient Human Motion Capture via LiDAR-Camera Integration

arXiv:2608.02285v1 Announce Type: new Abstract: We propose Sen-Cap, a Sensor-Flexible and Noise-Resilient 3D human motion Capture framework that integrates multi-modal data from LiDAR and camera. Whil

SG-Layout: Structured Scene Graph-Guided Layout Generation with LLMs

arXiv:2608.01106v1 Announce Type: new Abstract: Understanding and generating spatially coherent layouts from natural language remains a fundamental yet challenging task for large language models (LLMs

SG-WAM: Self-Guided World Modeling in Geometry-Aware Policy Space

arXiv:2608.01397v1 Announce Type: cross Abstract: World Action Models (WAMs) couple action generation with prediction of future states. Their effectiveness depends on whether future dynamics are model

SIGMA: Semantic Identifier Grouping for Molecular Autoregression

arXiv:2603.25062v2 Announce Type: replace Abstract: Autoregressive molecular models assign probability to molecular serializations even though chemical identity is invariant to serialization. Equivale

Slot2Text: Object-Centric Visual Tokenization for Efficient and Spatially Traceable Surgical MLLMs

arXiv:2608.01473v1 Announce Type: cross Abstract: Multimodal large language models (MLLM) for surgical scene understanding typically inject hundreds of dense visual tokens into a language model, leadi

SPAE: Spectrally Guided Autoencoder for Pretrained Visual Latents

arXiv:2608.01306v1 Announce Type: new Abstract: Latents from vision foundation models (VFMs) are semantically rich and well suited for visual understanding. Recent representation autoencoder methods s

Start Classifying: Categorical Critics for LLM Reinforcement Learning

arXiv:2608.02181v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) for large language models typically trains its critic by mean-squared-error (MSE) regression on scalar value targets.

STEAM:ASpatio-TEmporal Alignment Mixture-of-Experts Model with Hierarchical Pre-training for EEG Decoding

arXiv:2608.02070v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) have been widely used in motor rehabilitation, disease diagnosis, and other neural engineering scenarios. However, conv

StochSIPP: Safe Interval Path Planning in Stochastic Dynamic Environments

arXiv:2608.00792v1 Announce Type: new Abstract: Safe navigation under uncertain time-dependent blockage requires anticipating observations before committing to motion. We present StochSIPP, an exact c

Teleopit: A Full-Embodiment Humanoid Teleoperation System

arXiv:2608.01834v1 Announce Type: new Abstract: Humanoid teleoperation for demonstration collection requires coordinated whole-body motion, continuous dexterous hand control, and viewpoint control. Ex

Toward Plasticity-Preserving KL Regularization for Capability Retention in LLM Reinforcement Learning

arXiv:2608.01743v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central paradigm for large language model (LLM) post-training, but optimization toward new objectives can deg

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning

arXiv:2608.01488v1 Announce Type: new Abstract: Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy

Track-Guided Hierarchical Reinforcement Learning for Autonomous Vehicle Drifting with Minimum-Lap-Time Planning

arXiv:2608.00113v1 Announce Type: new Abstract: In Formula 1, drivers optimize racing lines within tire grip limits to minimize lap times; however, in rally racing, drivers intentionally break tractio

Training Small LLMs as Spatial Multi-Agent Policies

arXiv:2608.01425v1 Announce Type: cross Abstract: Training LLM-based multi-agent systems with multi-agent reinforcement learning is rapidly gaining traction, and a parallel line of work argues that su

Model Releases

Trustworthiness Costs of Domain Adaptation in Small Language Models:A Cross-Architecture Empirical Study

model-releasesarxiv-cs-cl

arXiv:2608.00042v1 Announce Type: new Abstract: Domain adaptation of small language models (SLMs) has emerged as a practical strategy for deploying capable NLP systems in resource-constrained, high-st

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability

arXiv:2608.02238v1 Announce Type: cross Abstract: Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning systems into high-stakes domains such as digital he

TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoning

arXiv:2510.03519v2 Announce Type: replace Abstract: Time series reasoning is crucial to decision-making in diverse domains, including finance, energy, and scientific discovery. While existing time ser

UDT: Reconciling U-Nets and Diffusion Transformers with Data-Adaptive Token Reduction

arXiv:2608.01298v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have emerged as a core architecture in generative modeling due to their scalability and adaptability to multimodal tasks.

Uncovering and Mitigating Positional Blind Spots in Vision-Language-Action Models

arXiv:2608.01573v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models achieve promising performance in robotic manipulation, typically measured by success rates aggregated over pr

Understanding and Correcting Low-Frequency Bias in EEG Foundation Model

arXiv:2608.01898v1 Announce Type: new Abstract: Increasing EEG pretraining data scale or model capacity does not consistently improve downstream performance. We identify a persistent low-frequency bia

Understanding and Overcoming Cross-modal Fusion Bias in Multimodal Anomaly Detection From A Fisher Information Perspective

arXiv:2608.00986v1 Announce Type: new Abstract: Current advancements in Multimodal Anomaly Detection (MAD) are largely driven by enhancing multimodal fusion, particularly through the integration of RG

Unleashing the Potential of Large Language Models: A Blueprint for Real-Time, Enterprise-Ready Deployments

arXiv:2608.00419v1 Announce Type: cross Abstract: Large language models deployed in real-time, regulated settings face knowledge staleness, catastrophic forgetting, hallucination, and weak feedback lo

Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning

arXiv:2608.02034v1 Announce Type: new Abstract: Multi-step returns accelerate reward propagation in off-policy reinforcement learning, but couple the evaluation of each decision to the suboptimal logg

USP-Mamba: Unmixing-Derived Spectral and Structural Prompting for Hyperspectral Image Super-Resolution

arXiv:2608.02401v1 Announce Type: new Abstract: Hyperspectral image super-resolution aims to reconstruct high-resolution imagery while preserving dense spectral information. Recently, Mamba-based mode

Verifier-Induced Support Reshaping in On-Policy Optimization

arXiv:2608.00220v1 Announce Type: cross Abstract: We show that on-policy reinforcement learning with verifiable rewards (RLVR) can improve the current objective while making successful behaviors for l

VLAGuard: A Framework for Evaluating and Mitigating Physical Attention Hijacking in Vision-Language-Action Robots within Wireless Sensor Networks

arXiv:2608.01028v1 Announce Type: new Abstract: Deploying Vision-Language-Action (VLA) robots as mobile edge nodes within wireless sensor networks (WSNs) requires robust protection against physical ad

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA

arXiv:2608.01035v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent paradigm for end-to-end autonomous driving; however, their efficient deployment is sev

Wasserstein mixing time of the unadjusted Langevin algorithm

arXiv:2608.02430v1 Announce Type: cross Abstract: We provide new estimates in Wasserstein distance for the asymptotic bias of the unadjusted Langevin algorithm, in the classical setting of log-smooth

Who Should Be Generated? Justifying Demographic Targets in Open-Ended Generation

arXiv:2608.02551v1 Announce Type: cross Abstract: Fairness evaluation concerns not only what a model produces, but also what its outputs ought to be compared against. When a model generates 'a CEO in

Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control?

arXiv:2608.02547v1 Announce Type: new Abstract: Action chunking---predicting and executing multiple actions instead of a single action---has proven to be a critical component for learning effective ro

World Action Models in Real Time: An Empirical Study of Smooth Execution via Asynchronous Deployment

arXiv:2608.01880v1 Announce Type: new Abstract: World Action Models generate fixed-horizon action chunks through iterative denoising, creating substantial inference latency that can cause pauses, stal

A detailed recap of the real-world target hacks by OpenAI and Anthropic models, exposing failures in AI alignment training and lack of meaningful supervision (Zvi Mowshowitz/Don't Worry About the Vase)

Zvi Mowshowitz / Don't Worry About the Vase: A detailed recap of the real-world target hacks by OpenAI and Anthropic models, exposing failures in AI alignment training and lack of meaningful supervisi

safetytechmeme

ActFovea: Runtime Safeguarding for VLA Policies via Spatiotemporal Visual-Action Consistency

arXiv:2607.29169v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies achieve strong performance in robotic manipulation but remain vulnerable to runtime disturbances that break the

safetyarxiv-cs-ai

Adaptive Emotional Video Captioning via Affective Heterogeneous Graph Reasoning and Multi-task Joint Learning

arXiv:2607.29045v1 Announce Type: new Abstract: Emotional video captioning (EVC) aims to describe a video with both factual correctness and affective expressiveness. It requires a model to perceive su

Adaptive FastOPD: Progress-Aware Rollout Horizon Expansion for Efficient On-Policy Distillation

arXiv:2607.29494v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense teacher supervision along student-generated trajectories, but its online rollout process incurs substantial

Adjudicated Captioning: Multi-Agent Alignment Scoring and Consensus-Distilled Beam Arbitration for Strict Zero-Shot Image Captioning

arXiv:2607.28986v1 Announce Type: cross Abstract: Zero-shot image captioning (ZIC) describes images without paired image-caption supervision during captioner training, relying on text-only corpora and

safetyarxiv-cs-ai

Advances, challenges, and opportunities for legged robots

arXiv:2607.28952v1 Announce Type: new Abstract: Humanoid and quadrupedal robots have the potential to revolutionize the way we work, interact, and coexist with intelligent machines. To understand thei

Agreement Is Not Quality: Blind Expert Verification of Human and LLM Qualitative Coding When Human Consensus Is Not Ground Truth

arXiv:2607.28890v1 Announce Type: cross Abstract: Evaluations of LLM-assisted qualitative coding almost universally measure model performance as agreement with human coders, a practice that presumes h

safetyarxiv-cs-ai