Search: “safety”

Vision-Language Models for Deployable Social Robot Navigation: Bridging Semantic Reasoning and Low-Level Control

arXiv:2606.28760v1 Announce Type: new Abstract: Social robot navigation (SRN) requires more than geometric path planning; it demands understanding human intentions, social norms, and contextual cues t

30 Jun 2026

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Artificial Intelligence Index Report 2026

DGX agent

arXiv:2606.15708v2 Announce Type: replace Abstract: Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it ca

safetyarxiv-cs-ai

29 Jun 2026

CacheMPC: Certified Cached Model Predictive Control for Quadruped Locomotion

arXiv:2606.28300v1 Announce Type: new Abstract: Model Predictive Control (MPC) is the standard predictive layer in hierarchical quadruped controllers, but the per-cycle QP solve limits the update rate

CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association

arXiv:2606.28179v1 Announce Type: cross Abstract: Identifying robust associations between cardiac imaging phenotypes and clinical diseases is fundamental to population-scale cardiovascular research an

Drifting in the Future: Stabilizing Path Following Drifting on High-Latency Vehicle Systems

arXiv:2606.27914v1 Announce Type: new Abstract: Autonomously controlling and handling a vehicle at and beyond its stability limit is a mathematically and computationally demanding task. Prior demonstr

Halt Fast! Early Stopping for Certified Robustness

arXiv:2606.27694v1 Announce Type: cross Abstract: Randomized Smoothing (RS) provides rigorous robustness guarantees for neural networks without architectural constraints, yet its adoption is limited b

hia-gat: A Heterogeneous Interaction-Aware Graph Attention Network For Frame-Level Traffic Conflict Risk Prediction On Freeways

arXiv:2606.27577v1 Announce Type: cross Abstract: This paper formulates frame-level freeway risk assessment as a multi-agent scene graph-level binary classification problem, where each video or trajec

Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs

arXiv:2601.21233v2 Announce Type: replace Abstract: Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-d

MetaBreak: Jailbreaking Online LLM Services via Special Token Manipulation

arXiv:2510.10271v2 Announce Type: replace-cross Abstract: Unlike regular tokens derived from existing text corpora, special tokens are artificially created to annotate structured conversations during

OverFlowLight: Real-Time Gridlock Prevention and Traffic Signal Optimization for Urban Intersections

arXiv:2606.27381v1 Announce Type: cross Abstract: Queue overflow, a severe consequence of urban traffic congestion, occurs when vehicle queues exceed intersection capacity, obstructing upstream traffi

Position: The Term 'Machine Unlearning' Is Overused in LLMs

arXiv:2606.27379v1 Announce Type: cross Abstract: Large language models increasingly face demands to 'forget' training data, knowledge, or behaviors due to regulatory deletion obligations, copyright/l

PRISON: Unmasking the Criminal Potential of Large Language Models

arXiv:2506.16150v4 Announce Type: replace-cross Abstract: As large language models (LLMs) advance, concerns about their misconduct in complex social contexts intensify. Existing research overlooked th

Regularized Reward-Punishment Reinforcement Learning

arXiv:2606.28152v1 Announce Type: new Abstract: We propose KL-Coupled Policy Regularization (KCPR), a policy coordination framework for Reward-Punishment Reinforcement Learning (RPRL). Based on KCPR,

ReWorld: Learning Better Representations for World Action Models

arXiv:2606.27504v1 Announce Type: new Abstract: World Action Models (WAMs) model future environment evolution under action conditioning, offering a scalable paradigm for autonomous driving. However, e

At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization

arXiv:2606.26396v1 Announce Type: new Abstract: Pre-trained transformers have demonstrated remarkable generalization abilities, at times extending beyond the scope of their training data. Yet, real-wo

Bridging Performance and Generalization in Reinforcement Learning for Agile Flight

arXiv:2606.27348v1 Announce Type: new Abstract: Autonomous drone racing is a fundamentally challenging regime for autonomous aerial robots, requiring time-optimal control while operating under persist

LAMP: Lane-Aligned Motion Primitives for Feasible Trajectory Prediction

arXiv:2606.26661v1 Announce Type: cross Abstract: Motion forecasting is essential for autonomous driving systems to enable safe decision-making and planning in complex driving scenarios. While existin

Radical AI Interpretability

arXiv:2606.26523v1 Announce Type: new Abstract: We develop a framework for interpreting AI systems as agents, drawing on the philosophical tradition of radical interpretation and the tools of mechanis

Reducing Conversational Escalation in Large Language Model Dialogue with Nonviolent Communication Constraints

arXiv:2606.26106v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in emotionally charged situations involving interpersonal conflict, frustration, and distress. Whil

Risk-Aware Selective Multimodal Driver Monitoring with Driver-State World Modeling

arXiv:2606.26922v1 Announce Type: cross Abstract: Continuous driver monitoring in automated vehicles requires low-latency inference while avoiding unsafe decisions under uncertain driver states. Large

Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery

arXiv:2606.26204v1 Announce Type: new Abstract: Floods frequently impact regions around the world. Rapid and accurate flood detection is crucial for emergency response and timely mitigation of human a

Adaptive-Horizon Conflict-Based Search for Closed-Loop Multi-Agent Path Finding

arXiv:2602.12024v3 Announce Type: replace Abstract: Multi-Agent Path Finding (MAPF) is a core coordination problem for large robot fleets in automated warehouses and logistics. Existing approaches are

Bias-Controlled Primal-Dual Natural Actor-Critic: Optimal Rates for Constrained Multi-Objective Average-Reward RL

arXiv:2606.25012v1 Announce Type: new Abstract: Many reinforcement learning (RL) problems in the infinite-horizon average-reward setting require optimizing multiple conflicting objectives while satisf

Model Releases

FinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming

model-releasesarxiv-cs-ai

arXiv:2606.19887v2 Announce Type: replace-cross Abstract: Existing safety benchmarks target general adversarial scenarios but miss finance-specific risks. Financial LLMs face regulatory compliance vio

Generative AI for Safe and Photorealistic Drone Light Shows

arXiv:2606.25458v1 Announce Type: new Abstract: Drone light shows are redefining aerial entertainment, yet their widespread adoption is bottlenecked by labor-intensive, manual animation. While generat

GUI agent: Guided Exploration of User-Sensitive Screens

arXiv:2606.25705v1 Announce Type: new Abstract: LLM agents are increasingly being used to automate tasks for users within an open GUI environment. They inevitably encounter screens containing user-sen

Long-Term Simulation Exposes Cognitive-Developmental Risks in AI Companions

arXiv:2606.25396v1 Announce Type: new Abstract: AI companions powered by large language models increasingly interact with cognition-developing users, including children and adolescents, creating risks

Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure

arXiv:2403.11425v4 Announce Type: replace-cross Abstract: Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk o

safetyarxiv-cs-cl

Phoneme-Level Mispronunciation Screening in Polish-Speaking Children with an Explainable Assistant

arXiv:2606.25181v1 Announce Type: cross Abstract: Early identification of speech sound errors in children is often limited by access to specialists, motivating lightweight screening tools that can ope

Reliability-Asymmetric Spacecraft Autonomy: Co-Designing a Capable Learned GNC Stack with a Verified, Adaptation-Aware Runtime Shield

arXiv:2606.25366v1 Announce Type: new Abstract: Deep-space missions need onboard autonomy that is both capable and certifiable. Rule-based autonomy is certifiable but brittle, while learned autonomy i

Reward-Conditioned Attention: How Reward Design Shapes What Autonomous Driving Agents See

arXiv:2606.25127v1 Announce Type: new Abstract: We investigate how reward design shapes the internal attention patterns of reinforcement learning agents trained for autonomous driving. Using three Per

Statistically Valid Hyperparameter Selection: From Tuning to Guarantees

arXiv:2606.25601v1 Announce Type: cross Abstract: Hyperparameter selection is a critical step in the deployment of modern artificial intelligence systems, given the need to tune degrees of freedom suc

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

arXiv:2601.16529v3 Announce Type: replace Abstract: Large language models (LLMs) deployed in clinical decision support may acquiesce to patient requests for care that conflicts with evidence-based gui

Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation

arXiv:2511.21056v2 Announce Type: replace-cross Abstract: Supervised fine-tuning (SFT) datasets are critical to the downstream performance of large language models, yet they often contain low-quality

safetyarxiv-cs-cl

Critique of Agent Model

arXiv:2606.23991v1 Announce Type: new Abstract: What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and

DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model

arXiv:2606.24051v1 Announce Type: new Abstract: Vision-Language-Action driving models convert a pretrained Vision-Language Model into a driving policy, allowing them to use world knowledge and follow

FT-WBC: Learning Fault-Tolerant Whole-Body Control for Legged Loco-Manipulation

arXiv:2606.24466v1 Announce Type: new Abstract: Legged manipulators combine the mobility of legged platforms with the manipulation capability of robotic arms. However, arm-induced Center-of-Mass shift

PixJail: Self-Evolving Paper-to-Pipeline Reproduction for Text-to-Image Jailbreak Evaluation

arXiv:2606.24081v1 Announce Type: cross Abstract: As Text-to-Image (T2I) jailbreak techniques evolve rapidly, existing benchmarks and reproduction workflows often struggle to keep pace. More important

Quant Convergence: Bridging Classical Value Investing and Modern Factor Models for Systematic Equity Selection

arXiv:2606.24575v1 Announce Type: new Abstract: Modern finance relies heavily on complex machine learning models to find patterns in the stock market. However, as these AI models get more complicated,

Selective Capability Unlearning in End-to-End Spoken Language Understanding

arXiv:2606.24063v1 Announce Type: cross Abstract: Modern spoken language understanding (SLU) systems are increasingly deployed in real-world settings, where specific functionalities may need to be rem

When Preferences Fail to Become Incentives: A Utility-Behavior Gap in Large Language Models

arXiv:2606.22974v2 Announce Type: replace Abstract: Recent work on preference elicitation in large language models (LLMs) has demonstrated that, when given a series of choices between two outcomes, LL

A Generative Model for Closed-Loop Microsimulation of Signalized Intersections

arXiv:2606.23588v1 Announce Type: new Abstract: Traffic microsimulators rely on hand-crafted behavior models that reproduce aggregate flow but miss the heterogeneous interactions between vehicles at s

Adversarial observations in probabilistic State-Space Models for robust Reinforcement Learning

arXiv:2606.20880v1 Announce Type: cross Abstract: Decision-making under partial or adversarial observability requires accurate inference of the environment's latent state and its associated uncertaint

BadDreamer: Transferable Backdoor Attacks against Video World Models for Autonomous Driving

arXiv:2606.21172v1 Announce Type: new Abstract: Video world models are increasingly used in autonomous driving to forecast future scene evolution and provide future-aware spatio-temporal representatio

Continuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting

arXiv:2606.21021v1 Announce Type: new Abstract: Long-horizon spacecraft trajectory forecasting suffers from error accumulation due to the absence of corrective observations in the forecast regime, mak

D2HDMap: Non-visible Driveline Map Prior for Online Vectorized HD Map Prediction

arXiv:2606.20725v1 Announce Type: new Abstract: Accurate, up-to-date representations of road structures are critical for the safe operation of autonomous vehicles. Existing systems rely either on cost

HoloAgent-0: A Unified Embodied Agent Framework with 3D Spatial Memory

arXiv:2606.23565v1 Announce Type: cross Abstract: LLM agents follow a practical execution loop in digital environments: they reason over structured states, invoke tools, inspect feedback, and revise a

Iterative Convex Optimization with Control Barrier Functions for Obstacle Avoidance among Polytopes

arXiv:2603.05916v2 Announce Type: replace Abstract: Obstacle avoidance of polytopic obstacles by polytopic robots is a challenging problem in optimization-based control and trajectory planning. Many e