Search: “safety”

RL-Ballast: Ship Ballast Water Path Planning and Clog Prediction via Reinforcement Learning

arXiv:2607.04906v1 Announce Type: new Abstract: Under the Shipping 4.0 paradigm, autonomous and reduced-crew vessels require intelligent internal systems to maintain operational safety and structural

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Safety

Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control

DGX agent

arXiv:2603.10938v2 Announce Type: replace-cross Abstract: Safe Reinforcement Learning from Human Feedback (RLHF) typically enforces safety through expected cost constraints, but the expectation captur

safetyarxiv-cs-ai

7 Jul 2026

Uncertainty Quantification for Regression: A Unified Framework based on kernel scores

arXiv:2510.25599v2 Announce Type: replace Abstract: Regression tasks, notably in safety-critical domains, require reliable uncertainty quantification, yet the literature remains largely classification

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks

arXiv:2510.16923v3 Announce Type: replace-cross Abstract: Deep learning models deployed in safety critical applications like autonomous driving use simulations to test their robustness against adversa

VISOR++: Universal Visual Inputs based Steering for Large Vision Language Models

arXiv:2509.25533v2 Announce Type: replace-cross Abstract: As Vision Language Models (VLMs) are deployed across safety-critical applications, understanding and controlling their behavioral patterns has

When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games

arXiv:2607.05132v1 Announce Type: cross Abstract: As large language models are deployed as autonomous agents that communicate intentions before acting, a critical safety question is whether agents tha

Rethinking Post-Hoc Calibration in Semantic Segmentation

arXiv:2607.01902v1 Announce Type: cross Abstract: Reliable confidence estimates are essential in semantic segmentation, especially in safety-critical settings where overconfident errors can mislead do

3 Jul 2026

Beyond the Prompt: Jailbreaking Function-Calling LLMs via Simulated Moderation Traces

arXiv:2607.00481v1 Announce Type: cross Abstract: Jailbreak attacks remain a critical threat to the safe deployment of large language models (LLMs). While prior work has primarily studied attacks and

Decentralized Geometric Control for Cable-Suspended Payload Transport with Adaptive Mass Estimation

arXiv:2607.00024v1 Announce Type: new Abstract: Cooperative aerial transport requires controllers that respect nonlinear manifold geometry, operate without centralized coordination, and respect operat

Evaluating Implicit Biases in LLM Reasoning through Logic Grid Puzzles

arXiv:2511.06160v2 Announce Type: replace Abstract: While recent safety guardrails effectively suppress overtly biased outputs, subtler forms of social bias emerge during complex logical reasoning tas

From Prediction Uncertainty to Conformalized Distance Fields for Safe Motion Planning

arXiv:2607.00776v1 Announce Type: new Abstract: Safe motion planning in dynamic environments requires reasoning about the uncertainty in predicted obstacle motion without sacrificing real-time perform

From Silos to Systems: Process-Oriented Hazard Analysis for AI Systems

arXiv:2410.22526v2 Announce Type: replace Abstract: To effectively address potential harms from Artificial Intelligence (AI) systems, it is essential to identify and mitigate system-level hazards. Cur

Learning Expert Strategy for Autonomous Robotic Endovascular Intervention via Decoupled Procedural Execution

arXiv:2607.00066v1 Announce Type: new Abstract: Endovascular interventions are high-stakes procedures requiring precise device operation within complex and tortuous vascular anatomies. Autonomous endo

DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction

arXiv:2606.31085v1 Announce Type: new Abstract: Drug-drug interaction (DDI) prediction is essential for medication safety, yet it requires reasoning over heterogeneous biomedical evidence whose releva

FLARE-AI: Flaw Reporting for AI

arXiv:2606.31567v1 Announce Type: cross Abstract: Flaw reporting for deployed AI systems is fundamental to identifying system failures and improving AI safety. Yet the AI reporting ecosystem is fragme

LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents

arXiv:2606.31045v1 Announce Type: new Abstract: Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory e

Stealthy Multi-Task Adversarial Attacks

arXiv:2411.17936v2 Announce Type: replace-cross Abstract: Deep neural networks are highly vulnerable to adversarial perturbations, raising serious safety concerns in the real-world systems. While prio

ActiveVital: Geometry-Aware Embodied Vital Signs Monitoring for Home Healthcare Robots

arXiv:2606.30275v1 Announce Type: new Abstract: Home robots require reliable vital signs monitoring to support long-term companionship and safety in daily environments, yet obtaining respiration and h

LaGen: Towards Autoregressive LiDAR Scene Generation

arXiv:2511.21256v2 Announce Type: replace Abstract: Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety

VISTA-DZ: Visual Semantic Trajectory Adaptation for Personalized Dilemma Zone Prediction

arXiv:2606.29548v1 Announce Type: cross Abstract: Driver decision making in the dilemma zone at signalized intersections is safety critical, as vehicles approaching a yellow signal must decide whether

Zero-Label Driving Scenario Complexity Detection via Joint Embedding Predictive Architecture

arXiv:2606.28383v1 Announce Type: new Abstract: Identifying complex and safety-critical driving scenarios in large unlabelled datasets is an important but expensive problem. Existing approaches rely o

OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators

arXiv:2606.28065v1 Announce Type: cross Abstract: Understanding model predictions is essential for physical applications, where outputs often inform safety-critical decisions, such as structural load

29 Jun 2026

PPO-EAL: Exact Augmented Lagrangian Proximal Policy Optimization for Safe Robotic Control

arXiv:2606.27861v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a promising solution to accomplish complex robotic control tasks; however, most of the current work ignores t

29 Jun 2026

Reasoning-Enhanced Rare-Event Prediction with Balanced Outcome Correction

arXiv:2601.16406v2 Announce Type: replace-cross Abstract: Rare-event prediction is critical in domains such as healthcare, finance, reliability engineering, customer support, aviation safety, where po

29 Jun 2026

Chai: Agentic Discovery of Cryptographic Misuse Vulnerabilities

arXiv:2606.26933v1 Announce Type: cross Abstract: AI-assisted vulnerability discovery has proven effective for bug classes like memory safety, where instrumentation confirms memory violations and effi

26 Jun 2026

HauntAttack: When Attack Follows Reasoning as a Shadow

arXiv:2506.07031v5 Announce Type: replace-cross Abstract: Emerging Large Reasoning Models (LRMs) consistently excel in mathematical and reasoning tasks, showcasing remarkable capabilities. However, th

26 Jun 2026

RecallRisk-BERT: A Multi-Task Framework for Post-Report Medical Device Recall Triage

arXiv:2606.27174v1 Announce Type: new Abstract: Medical device recalls are a critical regulatory mechanism for protecting patient safety. The growing volume of FDA recall records presents challenges i

26 Jun 2026

Model Releases

Falcon: Functional Assembly and Language for Compositional Reasoning in X-ray

model-releasesarxiv-cs-cv

arXiv:2606.25701v1 Announce Type: new Abstract: Conventional vision-language models are largely object-centric, focusing on detecting and describing individual entities. In safety-critical X-ray bagga

25 Jun 2026

The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar

arXiv:2606.26015v1 Announce Type: new Abstract: Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities a

25 Jun 2026

Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization

arXiv:2505.23866v2 Announce Type: replace Abstract: Deep neural networks have been increasingly used in safety-critical applications such as medical diagnosis and autonomous driving. However, many stu

25 Jun 2026

DDStereo: Efficient Dual Decoder Transformers for Stereo 3D Road Anomaly Detection

arXiv:2606.24805v1 Announce Type: new Abstract: Stereo-based 3D object detection still faces two critical safety challenges: real-time performance and open-set generalization. Existing stereo 3D metho

24 Jun 2026

One Year Later...The Harms Persist, But So Do We!

arXiv:2606.23884v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used for mental health-related conversations, yet safety safeguards remain inadequate an

24 Jun 2026

An LLM-Explainable DRL Framework for Passenger-Directed Autonomous Driving

arXiv:2606.20640v1 Announce Type: cross Abstract: Autonomous vehicles offer the potential for safer and more efficient mobility, yet public trust remains limited due to the lack of transparency in the

BayesFP: Posterior Estimation for Flow-Based Policies via Feynman-Kac Sampling

arXiv:2606.21014v1 Announce Type: new Abstract: Robots must generate trajectories that remain faithful to learned expert behavior while satisfying safety constraints and task-specific objectives speci

Conflict-Aware Switching for CBF-CLF-Based Multi-Goal Navigation

arXiv:2606.21577v1 Announce Type: new Abstract: Quadratic programs (QPs) using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are widely used for safe control in reach-and-avoi

Model Releases

CRAX: Fast Safe Reinforcement Learning Benchmarking

model-releasesarxiv-cs-lg

arXiv:2606.20376v2 Announce Type: replace Abstract: Safety is a core concern for deploying reinforcement learning (RL) agents in real-world domains such as robotics and autonomous driving. While bench

DBT-Bleed: Dual-Branch Temporal Modeling with Key-Frame Selection for Surgical Bleeding Detection

arXiv:2606.22829v1 Announce Type: new Abstract: Intraoperative Adverse Events (IAEs) detection is critical for improving surgical safety, with bleeding being among the most frequent events across many

From Driving Videos to Simulatable Scenarios

arXiv:2606.21993v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) face driving scenarios ranging from routine traffic to rare events. To assess safety it is crucial to reproduce these scenar

NegAS: Negative Label Guided Attention and Scoring for Out-of-Distribution Object Detection with Vision-Language Models

arXiv:2606.22537v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection is essential for ensuring the robustness and reliability of object detection systems deployed in safety-critical app

Neural Architecture Distributions: A New Paradigm for Stochastic Segmentation

arXiv:2606.21061v1 Announce Type: new Abstract: Stochastic segmentation seeks to represent multiple plausible masks for a single image, which is essential in safety- and quality-critical applications

Predicting cognitive load in immersive driving scenarios with a hybrid CNN-RNN model

arXiv:2408.06350v2 Announce Type: replace-cross Abstract: One debatable issue in traffic safety research is that cognitive load from sec-ondary tasks reduces primary task performance, such as driving.

Safe Few-Step Generation via Velocity Editing

arXiv:2606.23267v1 Announce Type: new Abstract: Flow matching has recently emerged as a strong paradigm for state-of-the-art text-to-image (T2I) generation, enabling high-quality generation with a sma

SPiralRoll: A Novel Adjustable-Stiffness Underactuated 3-DoF Joint with Torsion Springs for Rolling Robots

arXiv:2606.22443v1 Announce Type: new Abstract: Compliant mechanisms are important in robotics because they can improve adaptability, safety, and energy efficiency while reducing hardware complexity.

AutoMine Solution for AV2 2026 Scenario Mining Challenge

arXiv:2606.11874v1 Announce Type: new Abstract: With the development of autonomous driving systems, mining high-value, safety-critical, and planning-relevant scenarios from large-scale driving logs ha

Dummy Backdoor as a Defense: Removing Unknown Backdoors via Shared Internal Mechanisms for Generative LLMs

arXiv:2606.11648v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the safety and reliability of Large Language Models (LLMs), as they cause models to behave normally on clean

Human-Enhanced Loop Modeling (HELM): Agent-Based Finite Element Modeling of Concrete Bridge Barriers

arXiv:2606.12025v1 Announce Type: new Abstract: Finite element (FE) modeling of safety-critical infrastructure such as bridge barriers requires high-fidelity nonlinear dynamic analysis, yet the curren

JailbreakOPT: Tool-Assisted Iterative Jailbreak Prompt Optimization

arXiv:2606.11425v1 Announce Type: cross Abstract: Jailbreak attacks expose persistent safety weaknesses in large language models (LLMs), but existing stateless single-turn methods face a trade-off: ha

One Jailbreak, Many Tongues: Learning Language-Insensitive Intention Representations for Multilingual Jailbreak Detection

arXiv:2606.11202v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications for global multilingual users, yet safety training remains concentrated in domina