Search: “safety”

AuthGateBench: Benchmarking LLMs as Authorization Gate

arXiv:2610.16426v1 Announce Type: new Abstract: Automated approval systems let coding agents execute high-risk actions with minimal human oversight by delegating the authorization decision to a classi

15 Oct 2026

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CockpitHAT: Dependency-Graph-Driven Hierarchical Attribution for Embodied Multi-Agent Cockpits

DGX agent

arXiv:2608.01805v2 Announce Type: replace Abstract: LLM multi-agent systems suffer from Correctness Collapse, where high task-level accuracy conceals severe process-level failures. This is especially

model-releasesarxiv-cs-ai

15 Oct 2026

The Reasoning Trap -- Logical Reasoning as a Mechanistic Pathway to Situational Awareness

model-releasesarxiv-cs-cl

arXiv:2603.09200v2 Announce Type: replace-cross Abstract: Situational awareness, the capacity of an AI system to recognize its own nature, understand its training and deployment context, and reason st

15 Oct 2026

Towards Merging-conditional Backdoor Unalignment against Large Language Models

arXiv:2610.14701v1 Announce Type: cross Abstract: Model merging has become widely adopted for enhancing the task-specific performance of Large Language Models (LLMs) without additional training. While

15 Oct 2026

agent-risk: Risk Assessment for Changes to AI Agents

arXiv:2610.16280v1 Announce Type: cross Abstract: Before changing a deployed AI agent (a stricter safety gate, a new model), organizations must approve the change, starting from existing logs. Extendi

Certified Robustness via Sparse Second-Order Cone Relaxations

arXiv:2610.16016v1 Announce Type: new Abstract: Certified robustness is critical for deploying neural networks in safety-sensitive settings, but computing exact certificates typically requires solving

Refuses in Chat, Complies with Arms: LLM Refusal Does Not Survive Robot Control

arXiv:2610.14043v1 Announce Type: cross Abstract: Frontier language models reliably refuse to explain how to cause physical harm. We ask whether this refusal survives when the same models control a ro

RIECNN: Real-Time Image Enhanced CNN for Traffic Sign Recognition

arXiv:2610.15127v1 Announce Type: new Abstract: Traffic sign recognition plays a crucial role in the development of autonomous cars to reduce the accident rate and promote road safety. It has been a n

A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation

arXiv:2610.11149v1 Announce Type: new Abstract: Video anomaly detection (VAD) is a fundamental and safety-critical task in computer vision. Recent generative approaches detect anomalies from a distrib

9 Oct 2026

Ecology of AI Agents: Collaboration Creates a Population Threshold for Takeoff

arXiv:2610.12436v1 Announce Type: new Abstract: AI agents can now conduct real-world cyberattacks, scale up capabilities with the number of agents, and collectively pursue misaligned goals to obtain r

9 Oct 2026

Localize Any Object in X-Ray Security Scans without Human Annotation

arXiv:2610.07326v1 Announce Type: new Abstract: Universal object localization in X-ray security inspection is critical for automated threat detection in safety-critical venues. However, unlike everyda

local-aiarxiv-cs-cv

7 Oct 2026

Too Categorical to be Human: Emotion Concepts in LLMs and Humans

arXiv:2508.05880v3 Announce Type: replace-cross Abstract: Understanding human emotions is central to user-facing AI applications, safety alignment, and the simulation of human behavior. As emotional s

7 Oct 2026

What the Elevation Map Cannot See: Semantic-Aware Locomotion and Execution-Aware Navigation for Humanoid Robot

arXiv:2610.07396v1 Announce Type: new Abstract: Navigation for humanoid robots is critical, yet large-scale evaluation on physical hardware is often impractical due to cost and safety concerns, making

7 Oct 2026

Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based

6 Oct 2026

Reachability-Guided Sequential Quadratic Programming-Guarded Model Predictive Path Integral for Safe Nonlinear Predictive Control

arXiv:2610.04406v1 Announce Type: new Abstract: Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to

local-aiarxiv-cs-ro

6 Oct 2026

MiDShip: Multimodal Dataset of Ship Cargo Hold Structures for Engineering Design

arXiv:2610.02214v1 Announce Type: cross Abstract: Ship structures govern vessel strength, safety, and manufacturability, but their design must satisfy hundreds of classification society requirements,

5 Oct 2026

Conflicting Supervision Moves Commitment, Not Capability: A 12.29{sigma} arrangement effect that is exactly zero under a convention-agnostic score

arXiv:2610.00234v1 Announce Type: new Abstract: 'Train a model on the same problems written under two incompatible conventions, both correct, and ask what the ordering of that data writes into the par

2 Oct 2026

HADRec: A Hierarchy-Aware Drug Recommendation Framework by Fusing Molecular Knowledge and Electronic Health Record

arXiv:2610.00984v1 Announce Type: new Abstract: Accurate medication recommendation is central to clinical decision-making, directly determining therapeutic efficacy and patient safety. However, existi

2 Oct 2026

Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving

arXiv:2609.38862v1 Announce Type: cross Abstract: Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computatio

Inference-Layer Security: Defending Against Adversarial Inference and Infrastructure Abuse

arXiv:2609.38239v1 Announce Type: cross Abstract: A Technical Report: Operating a large language model (LLM) as a service requires more than inference infrastructure: the provider must also defend aga

PrivMeSA: Privacy-Aware Self-Evolving Multi-Agent System for Medicine via Local-Remote LLM Collaboration

arXiv:2609.38458v1 Announce Type: new Abstract: Clinical large language model (LLM) agents deployed locally can consult more capable remote models, but doing so risks exposing patient information. Pri

SceneJail: Exploiting Video Scenario Context to Jailbreak Multimodal LLMs

arXiv:2609.38899v1 Announce Type: cross Abstract: Video Multimodal Large Language Models (Video-MLLMs) support reasoning over video inputs, yet remain vulnerable to jailbreak attacks that elicit polic

SEABench: Benchmarking Endogenous Misalignment In Self-Evolving Agents

arXiv:2609.35596v2 Announce Type: replace-cross Abstract: Self-evolving LLM agents have gained prominence for their ability to improve after deployment by modifying their harness, including their cont

Sparse Planner: A Hybrid Planner for Efficient Sampling via a Conditional Variational Autoencoder

arXiv:2609.39570v1 Announce Type: new Abstract: Trajectory planning is a core component of autonomous driving systems, where real-time performance and solution quality directly affect safety and relia

Does the Unsafe Gradient Survive a Conversation? On the Fragility of Gradient-Based Jailbreak Detection in Multi-Turn Dialogue

arXiv:2609.36849v1 Announce Type: cross Abstract: Safety-aligned language models are commonly deployed as multi-turn assistants, which lets adversaries spread unsafe intent across several user turns i

From Concept Erasure to Style Purification: Contrastive Eigenbases for Artist Style Protection

arXiv:2602.08059v2 Announce Type: replace-cross Abstract: Text-to-image diffusion models can reproduce specific artists visual styles at extremely low cost, raising copyright and deployment safety con

local-aiarxiv-cs-ai

Guard Models Are Overconfident Where Base Models Are Uncertain

arXiv:2609.36477v1 Announce Type: cross Abstract: Guard models are used as safety classifiers, with confidence scores driving downstream moderation decisions. We evaluate five guard models for prompt

local-aiarxiv-cs-ai

Suppression Is Not Forgetting: Residual Recoverability in Visual Concept Unlearning for VLMs

arXiv:2604.03114v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) may need to forget visual concepts after deployment because of privacy, copyright, licensing, safety, or policy

Where Root Cause Analysis Fails: A Retrieval-Reranking Decomposition

arXiv:2609.36686v1 Announce Type: new Abstract: Identifying the root cause of an anomaly among hundreds of sensors is critical for preventing safety incidents and costly downtime in complex monitored

A Solvable Theory of Pre-training Data Poisoning: Regime-Dependent Scaling Exponents

arXiv:2609.32288v1 Announce Type: new Abstract: Pre-training data poisoning of large language models is usually studied using targeted backdoors and their survival through safety post-training, which

local-aiarxiv-cs-lg

BR-MPPI: Barrier-Rate Guided MPPI for Enforcing Multiple Inequality Constraints with Learned Signed Distance Fields

arXiv:2506.07325v2 Announce Type: replace Abstract: Model Predictive Path Integral (MPPI) control provides a sampling-based framework for optimal control, while Control Barrier Functions (CBFs) provid

DBCF: Dual-Branch Complementary Fusion of Foundation Models for Generalized Deepfake Detection

arXiv:2609.34720v1 Announce Type: new Abstract: As image generation and editing technologies have progressed substantially, facial forgeries pose significant challenges to privacy and public safety. D

Do World Models Learn Global Understanding?

arXiv:2609.34058v1 Announce Type: new Abstract: AI systems often feel brittle and fragmented. A large language model (LLM) may correctly explain a concept but fail to apply it, or follow safety instru

local-aiarxiv-cs-lg

Relative Density Ratio Optimization for Stable and Statistically Consistent Model Alignment

arXiv:2604.04410v2 Announce Type: replace Abstract: Aligning language models with human preferences is essential for ensuring their safety and reliability. Although most existing approaches assume spe

SAGE: Symbolic Action-Gating and Editing for LLM Task Planners

arXiv:2609.34268v1 Announce Type: new Abstract: Large language models (LLMs) are now the default cognitive core of embodied household agents, yet the plans they emit are rarely checked against a groun

Cosine Similarity Is Not Evidence: Measuring the Noise Floor of Interpretability Transfer Under Quantization

arXiv:2609.30275v1 Announce Type: new Abstract: A statistic reported without the quantity needed to interpret it is not evidence. We develop that thesis for a concrete practice in AI safety. Interpret

28 Sept 2026

HyperErase: Scale-Calibrated Hypernetwork for Multi-Concept Erasure in Text-to-Image Models

arXiv:2609.31154v1 Announce Type: new Abstract: Recent advances in text-to-image (T2I) generation have substantially improved visual synthesis, but have also raised increasing safety concerns due to t

28 Sept 2026

Words Speak Louder Than Order: A Behavioral Evaluation of Gemma 4

arXiv:2609.30716v1 Announce Type: cross Abstract: When a language model receives two conflicting documents as input, how does it decide which one to prioritize? Does it rely on how the sources are fra

28 Sept 2026

An Explainable DistilBERT-BiLSTM-Attention Framework for Binary and Multi-Class Hate Speech Detection

arXiv:2609.28703v1 Announce Type: cross Abstract: Hate speech on social media poses serious risks to social harmony, mental well-being, and public safety, making its timely and accurate detection esse

25 Sept 2026

Instrumental Monitor Evasion Emerges Under Ordinary Task Pressure

arXiv:2609.30217v1 Announce Type: cross Abstract: A central concern in AI safety is that agents may treat oversight as an obstacle when it conflicts with completing their goals. We study instrumental

25 Sept 2026

Refusing Everything Looks Safe: Restoring the Benign Arm to Encoded-Prompt Evaluation

arXiv:2609.26176v2 Announce Type: replace-cross Abstract: Encoded-prompt attacks are evaluated almost entirely on their harmful arm: a benchmark sends obfuscated harmful requests and reports how often

25 Sept 2026

Toward Auditable and Calibrated AI for Dementia-Related Crash Severity Prediction: A Selective Deferral Framework to Support Human Review

arXiv:2609.22694v1 Announce Type: new Abstract: Public crash databases increasingly support automated safety analysis, but crash severity prediction remains difficult to translate into public-sector d

23 Sept 2026

FeasibleFlow: One-Step Joint Transport of Configuration Feasibility and Trajectories for End-to-End Driving

arXiv:2609.23488v1 Announce Type: new Abstract: End-to-end autonomous driving maps current observations directly to future trajectories, yet those trajectories must remain valid as the scene evolves.

22 Sept 2026

DPed-VLN: A Benchmark for Socially Compliant Vision-and-Language Navigation in Dynamic Pedestrian Environments

arXiv:2609.21504v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) has advanced rapidly in static indoor environments, but robots operating in human-populated spaces must ground lang

21 Sept 2026

TERMon: Detecting Persistent Behavioral Threats in Edge AI via Hardware-Native Ternary Runtime Monitor

arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-contro

local-aiarxiv-cs-ai

21 Sept 2026

HALT: Hallucination Assessment via Log-probs as Time series

arXiv:2602.02888v2 Announce Type: replace-cross Abstract: Hallucinations remain a major obstacle for large language models (LLMs), especially in safety-critical domains. We present HALT (Hallucination

17 Sept 2026

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

arXiv:2609.15297v1 Announce Type: new Abstract: In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. I

15 Sept 2026

KnowBench: Effort Reduction as a Unified, Deployment-Grounded Benchmark for Clinical AI

arXiv:2609.15794v1 Announce Type: new Abstract: Clinical AI systems are evaluated with instruments built for research settings (reference-based similarity metrics and expert rubric panels) that measur