Search: “safety”

AutoAgent0: An Agentic Runtime for Safe Closed-Loop Driving

arXiv:2610.18866v1 Announce Type: new Abstract: Safe autonomous driving requires more than accurate planning at a single frame: it demands reliable closed-loop execution in dynamic environments. Altho

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Beyond Safe Execution: Safe Online Reinforcement Learning for Autonomous Driving with Value Calibration and Adaptive Guidance

DGX agent

arXiv:2610.17799v1 Announce Type: new Abstract: Online reinforcement learning (RL) enables driving policies to adapt to changing deployment conditions, but requires safe exploration throughout trainin

safetyarxiv-cs-ro

14 Oct 2026

Beyond the End-Effector: Learning Whole-Arm Contact Manipulation from Human Demonstrations

arXiv:2610.17802v1 Announce Type: cross Abstract: Robot manipulation has traditionally relied on end-effector-centric interactions. In contrast, humans routinely exploit whole-arm contacts to improve

Beyond User-Side Defenses: Image Protection in Open-Weight Diffusion Models

arXiv:2610.16835v1 Announce Type: cross Abstract: Model providers can support image protection, but open-weight deployment introduces practical constraints. We propose four requirements: protection ef

Building age estimation based on widely available multi-source1 geospatial data

model-releasesarxiv-cs-cv

arXiv:2610.16320v1 Announce Type: new Abstract: Building age is fundamental for urban infrastructure safety, operation, and planning, as it directly affects structural safety, and sustainable developm

Hallucination-aware Faithful Reasoning in Remote Sensing

arXiv:2610.18369v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated promising capabilities for remote sensing reasoning, yet they frequently generate visually un

Hiking in the Wild: A Scalable Perceptive Parkour Framework for Humanoids

arXiv:2601.07718v2 Announce Type: replace Abstract: Achieving robust humanoid locomotion in complex, unstructured environments requires transitioning from reactive proprioception to proactive percepti

Reach-Avoid Certificates for Contact-based Stochastic Hybrid Systems

arXiv:2610.17308v1 Announce Type: cross Abstract: This work studies certified reach-avoid control of stochastic hybrid systems in which a stochastic differential equation governs continuous flow and a

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

model-releasesarxiv-cs-lg

arXiv:2610.14474v1 Announce Type: new Abstract: Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-m

Semantic Edge-Cloud Communication for Real-Time Urban Traffic Digital Twins

arXiv:2610.14187v1 Announce Type: cross Abstract: Urban traffic systems are becoming increasingly complex, demanding real-time traffic perception, proactive collision prediction, and intelligent manag

ABLEIST: Intersectional Disability Bias in LLM-Generated Hiring Scenarios

arXiv:2510.10998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly under scrutiny for perpetuating identity-based discrimination in high-stakes domains such as hir

12 Oct 2026

Learning to Report Unsafe Tasks in a Multi-Agent Game

arXiv:2610.09002v2 Announce Type: replace Abstract: When a team of agents shares a reward for completed tasks, reporting and stopping unsafe work reduces the team's reward. Random audits that penalize

12 Oct 2026

When MLLMs miss what humans read: diagnosing and learning to read squint text

arXiv:2610.13465v1 Announce Type: cross Abstract: Multimodal LLMs can fail to read text embedded in an image's coarse structure (text a human recovers by squinting) and report that no text is present.

12 Oct 2026

Safe Actions Alone Do Not Ensure Safe Agents: Identifying Unfulfilled Obligations with Guard Models

model-releasesarxiv-cs-ai

arXiv:2610.11773v1 Announce Type: new Abstract: Guard models are increasingly used to safeguard LLM-based agents, primarily by identifying actions that agents are forbidden to perform. However, identi

9 Oct 2026

Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation

model-releasesarxiv-cs-ro

arXiv:2610.09302v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce ra

Beyond the Sycophancy Score: How Task, Model, and Pressure Shape LLM Yielding

arXiv:2610.08840v1 Announce Type: new Abstract: Large language models (LLMs) often abandon a correct answer, or endorse a user's position, once the user pushes back. This behavior, called sycophancy,

safetyarxiv-cs-cl

Careful Judge: Safe and Efficient Human-AI Collaborative Decision Making

arXiv:2610.09043v1 Announce Type: cross Abstract: In human-AI collaborative decision making, human review can prevent unsafe AI decisions, but each human judgment is costly. Treating human interventio

Is Word Error Rate Enough? Rethinking Privacy Evaluation in Speech with Entity-Aware Metrics

arXiv:2610.08831v1 Announce Type: cross Abstract: As the use of smart devices continues to increase, their potential to capture sensitive speech content raises growing privacy concerns. It is therefor

safetyarxiv-cs-cl

Safe on Average, Unsafe in the Tail: When Is the Episodic-Cost Tail Controllable?

arXiv:2610.09508v1 Announce Type: new Abstract: Safe reinforcement learning seeks policies that maximize return while satisfying constraints on cumulative cost. Most methods impose these constraints o

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their …

We have a choice in front of us. In my latest op-ed for Transformer, I invite employees of frontier AI companies to ask themselves if their work is truly leading us toward a safer future. Reflecting o

safetyyoshua-bengio--x

Auditable Claims about AI Agents

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

Hearing Like Humans? Sound Symbolism and Perceptual Alignment in Speech Language Models

arXiv:2607.10162v2 Announce Type: replace-cross Abstract: Sound symbolism, the human tendency to map speech sounds to perceptual qualities such as roundness or sharpness, arises primarily from the aco

safetyarxiv-cs-cl

Linear Bandits under Exact Sliding-Window Constraints

arXiv:2610.08745v1 Announce Type: new Abstract: We study linear bandits under exact sliding-window constraints, where every consecutive block of actions must belong to a prescribed feasible set. In th

Micro Neural Policies for Safe Real-Time Robotic Control

arXiv:2610.08541v1 Announce Type: cross Abstract: In this paper, we investigate the synthesis of Micro Neural Policies (MNP) to enable safe and robust real-time robotic control on computationally cons

Toward Alignment Scaling Laws: A Framework and First Preregistered Measurements

arXiv:2610.08540v1 Announce Type: new Abstract: Whether alignment gets easier or harder as models grow is often argued from isolated findings, as if alignment were one property. We treat it as a famil

Where Does the Audio Jailbreak Live? A Controlled Frequency-Depth Audit of AdvWave-P on Qwen2-Audio

arXiv:2610.07005v1 Announce Type: cross Abstract: We audit frequency and decoder-depth claims for AdvWave-P, an additive audio jailbreak, on Qwen2-Audio. The protocol masks frequency components of the

A Safe Action Is Not Enough: Feasible-Future Decoding for Vision-Language-Action Policies

arXiv:2610.05166v1 Announce Type: cross Abstract: A safe action is not necessarily a viable one. Under a frozen vision-language-action (VLA) policy, an action can be likely and locally admissible yet

Beyond In-Distribution Preservation: Recovering Generalization in Quantized VLAs via Vulnerability-Oriented Tuning

arXiv:2610.05745v1 Announce Type: new Abstract: Post-training quantization has been shown to preserve VLA performance under standard evaluation conditions, but whether it preserves the full-precision

ForeAct3D: Policy-Grounded Future World Modeling for VLA Policies

arXiv:2610.04607v1 Announce Type: cross Abstract: Robots need to anticipate how their actions will change the world, since manipulation success hinges on the resulting contacts and object motions. How

From Kinematic Motion Planners to Dynamic Autonomous Navigation with Obstacle Avoidance (Extended version)

arXiv:2503.17589v3 Announce Type: replace Abstract: Kinematic motion planners are among the most widely used control approaches in robotic applications. By modeling the robot as a first-order system,

Monitorability Disposition in Large Reasoning Models

arXiv:2610.04914v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of large reasoning models (LRMs) is a common way to detect misbehavior in real-world practice. However, current

Recurrent Latent Visual Search for GUI Grounding

arXiv:2610.05185v1 Announce Type: new Abstract: GUI grounding is a critical capability for GUI agents powered by vision-language models, helping them execute user instructions by locating the correspo

Safe Ergodic Control for Multi-Robot Systems via Quadratic Programming

arXiv:2610.05258v1 Announce Type: new Abstract: Ergodic control drives robots to spend time in each region in proportion to a spatial distribution of interest, making it well suited for dense spatiote

The Arbitrary-Placement Problem in Entropy-Minimizing Selection, and a Residual-Entropy Formulation

arXiv:2610.05925v1 Announce Type: new Abstract: Entropy-based selection objectives suffer from a fundamental degeneracy: minimizing Shannon entropy H(p_A) rewards confident selection regardless of whe

From Migration to Calibration: Preserving Agent Capabilities across Models, Jurisdictions, and Scale

arXiv:2609.35149v2 Announce Type: replace Abstract: Deploying, migrating, or scaling an agent can change its model, harness, infrastructure, application, and intended users. We formulate agent calibra

5 Oct 2026

Mitigating Private Data Leakage in LLMs with Whiteout

arXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit

5 Oct 2026

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

Capabilities Ain't All You Need: Measuring Propensities in AI

model-releasesarxiv-cs-ai

arXiv:2602.18182v5 Announce Type: replace-cross Abstract: AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasin

Constant-Time Planning for Chaining Collision-free Motion to Manipulation Behaviors

arXiv:2512.00939v3 Announce Type: replace-cross Abstract: Recent progress in contact-rich robotic manipulation has been striking, yet most deployed systems remain confined to simple, scripted routines

CortexBridge: Cortical Alignment of EEG Montages for Foundation Models

arXiv:2610.01124v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models are often pretrained with a fixed channel vocabulary or a limited set of montages, making transfer diffic

Deny Without Disabling: Authorization-Paired Evaluation and Control for Multi-Agent Systems

arXiv:2610.00371v1 Announce Type: cross Abstract: Multi-agent systems derive their capabilities from sharing evidence, delegating tasks, and combining information across agents. The same process creat

End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systems

arXiv:2610.01746v1 Announce Type: cross Abstract: Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offe

Fault-Tolerant Budget Conservation in Distributed Multi-Agent Delegation

arXiv:2610.00349v1 Announce Type: new Abstract: Resource limits are becoming an authorization boundary for AI agents that delegate work across concurrent and failure-prone workers. Parent-child alloca

Knowing When to Yield: Grounded Arbitration of User Corrections in Text-Based Embodied Agents

arXiv:2610.00282v1 Announce Type: new Abstract: How should an embodied agent respond when a person's correction may be wrong? We formulate grounded correction arbitration as a choice among accepting,

MOMAT: Mixture of Multiple Atlases for Low-Power Jailbreak Defense of Quantized LLMs

arXiv:2610.01058v1 Announce Type: cross Abstract: Quantized large language models are increasingly deployed on edge devices for their low latency and energy efficiency. However, model quantization wea

No One Architecture Fits All: A Cross-Environment Evaluation of Hierarchical Red Team Agents

arXiv:2610.00557v1 Announce Type: cross Abstract: Autonomous red team agents increasingly stress-test AI-enabled cyber defenses by planning strategy and executing multistage attacks. Reinforcement lea

Removing the NEEDLE in the Haystack: Backdoor Removal in LLMs via Weight Orthogonalisation

arXiv:2610.00348v1 Announce Type: cross Abstract: Backdoor attacks can be implanted in Large Language Models (LLMs) during training, causing unwanted behaviour when a trigger appears in the input. Exi