Search: “safety”

WTAF - in literally the last hour, three new distinct insane OpenAI stories just broke: 1. OpenAI said they notified 'dozens of third partie…

WTAF - in literally the last hour, three new distinct insane OpenAI stories just broke: 1. OpenAI said they notified 'dozens of third parties' in safety and security incidents (likely similar to what

safetygary-marcus--x

25 Sept 2026

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An Open Pipeline and Dashboard for Systemic-Risk Evidence under the EU AI Act's Code of Practice

DGX agent

arXiv:2609.28335v1 Announce Type: new Abstract: Claims about AI safety reach audiences well beyond the AI community, yet many rely on opaque evidence or static assessments, when supporting evidence is

model-releasesarxiv-cs-ai

24 Sept 2026

CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation

arXiv:2609.27825v1 Announce Type: new Abstract: Anomalous time series play a critical role in safety-critical domains, yet they are inherently scarce, heterogeneous, and costly to obtain. Existing tim

Faithful, Interpretable Chest X-ray Diagnosis with Artifact-free B-cos Networks

arXiv:2507.16761v3 Announce Type: replace Abstract: Faithfulness and interpretability are essential for deploying deep neural networks (DNNs) in safety-critical domains such as medical image analysis.

Hard Negatives Reveal What Easy Negatives Hide: Cross-Lingual Harmfulness Representations Degrade with Resource Tier Under Hard Negatives

arXiv:2609.27758v1 Announce Type: cross Abstract: Safety alignment in large language models is trained primarily in English, and recent work reports that the underlying harmfulness representation surv

OpenAI agents hacked an Australian government website in search for data

OpenAI's artificial intelligence agents hacked an Australian government website and attempted to breach numerous other government and university websites. The attack appears to be the first confirmed

safetythe-verge-ai

Researchers link more cyberattacks to OpenAI agent swarm

A research group has linked three more hacking campaigns to rogue artificial intelligence agents. Transluce, a nonprofit AI safety organization, detailed its findings on Wednesday. Its researchers det

safetysiliconangle

Safe learning-based control via function-based uncertainty quantification

arXiv:2604.01173v2 Announce Type: replace-cross Abstract: Uncertainty quantification is essential when deploying learning-based control methods in safety-critical systems. This is commonly realized by

Teach-to-Crash: A Closed-Loop Student-Teacher LLM Framework for Collision-Inducing Test Scenario Generation

arXiv:2609.27296v1 Announce Type: cross Abstract: Validating Autonomous Driving Systems (ADS) in simulation requires testing architectures that can discover rare, safety-critical failures while genera

'What's That Sound?': A Versatile, Robust, and Lightweight Convolutional Transformer for Environment Sound Recognition

arXiv:2609.27762v1 Announce Type: cross Abstract: The conventional hearing aid is both costly and lim- ited in usage, as it is not intended to detect non-speech audio. Our objective is to develop a ma

Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech

arXiv:2609.24016v1 Announce Type: new Abstract: Commercial large language models are increasingly deployed across African fintech infrastructure for fraud detection and customer communication, yet no

23 Sept 2026

SafeLoop: Risk-Aware Rollback for Vision-Language-Action Manipulation

arXiv:2609.26313v1 Announce Type: new Abstract: Recent vision-language-action (VLA) models are promising for general-purpose manipulation, but long-horizon execution remains fragile. Small state-estim

23 Sept 2026

Analyzing Public Discourse on Urbanism: Topic Clustering, Sentiment Analysis and Retrieval-Augmented Generation using YouTube Comments

arXiv:2609.22705v1 Announce Type: new Abstract: Online discourse about urban issues - walkability, cycling infrastructure, public transit, housing density, and street safety - is voluminous but unstru

Barrier Certificate Synthesis for Non-Polynomial Robotic Dynamics via Polynomial Lifting

arXiv:2609.22885v1 Announce Type: new Abstract: Safe operation of robotic systems requires trajectories to remain within a prescribed safe set under admissible control inputs. Barrier certificates pro

Local Ai

BarrierFormer: Transformer-Guided Predictive Barrier Enforcement for Safe Robot Control

arXiv:2609.23896v1 Announce Type: new Abstract: Control barrier functions (CBFs) have become one of the most popular tools for encoding and enforcing state constraints in safety-critical robotics. Sta

local-aiarxiv-cs-ro

Computationally efficient safe exploration in reinforcement learning

arXiv:2609.22919v1 Announce Type: new Abstract: Reinforcement learning in real-life applications requires safety guarantees during exploration. Typical reinforcement learning algorithms do not provide

From Trait Vectors to Circuits: Tracing Refusal and Sycophancy Through Language Models

arXiv:2609.22224v1 Announce Type: new Abstract: A direction in activation space that changes safety-relevant behavior when steered is not necessarily one the model uses to produce that behavior on its

Industrial Kinematic Trajectory Model (IKTM): Coordinate-Free Autoregressive Generator

arXiv:2609.22173v1 Announce Type: new Abstract: Mobility simulation supports logistics, safety, and communications planning in industrial environments such as ports, mines, and airports. Existing traj

Intelligent Degradation Monitoring in Lithium-ion Batteries via Discharge Incremental Capacity Feature Estimation

arXiv:2609.22843v1 Announce Type: cross Abstract: Accurate and timely detection of degradation in lithium-ion batteries is crucial to ensure safety, reliability, and longevity in high-demand applicati

Last October, AIs could automate 2.5% of randomly chosen remote projects. Our latest Remote Labor Index results show that GPT-6 Astra can no…

Last October, the Center for AI Safety (CAIS) reported that AIs could automate only 2.5 % of randomly selected remote projects. Updated results from the Remote Labor Index, posted on September 22, 202

safetydan-hendrycks--x

Generative Artificial Intelligence Chatbots for Motivational Interviewing: A Scoping Review From System Design to Intervention Outcomes

arXiv:2609.20902v1 Announce Type: new Abstract: Motivational interviewing (MI) is a collaborative approach to elicit autonomous motivation for health behavior change. Generative AI (GenAI) offers new

Gradient-Stable Attention Heads Signal LLM Correctness

arXiv:2602.13699v2 Announce Type: replace Abstract: Large language models (LLMs) often generate plausible yet incorrect answers, posing risks in safety-critical settings such as medicine. Human evalua

RAYA: Learning Where and When to Intervene for Robot Recovery

arXiv:2609.21690v1 Announce Type: new Abstract: A robot can predict failure and still be unable to prevent it. By the time a safety mechanism reacts, the nominal plan may already have spent the contro

Uni-PrevPredMap: Extending PrevPredMap to a Unified Framework of Prior-Informed Modeling for Online Vectorized HD Map Construction

arXiv:2504.06647v4 Announce Type: replace Abstract: Safety-critical autonomous driving motivates the effective use of prior information. For online vectorized HD map construction, temporal predictions

AgentPProf: Semantic Profiler for Long Horizon AI Agents

arXiv:2609.20301v1 Announce Type: new Abstract: AI agents increasingly orchestrate long-running activities with users, tools, and system resources for days and weeks. To improve agent quality, safety,

Design and Experimental Validation of a 3D Printed Torsional Series Elastic Actuator for Safe Human Robot Interaction

arXiv:2609.19367v1 Announce Type: new Abstract: Ensuring intrinsic safety in physical human robot interaction (pHRI) is a critical requirement for social and service robots. While Series Elastic Actua

Learn Before You Judge: Progressive Knowledge-to-Decision Alignment for Explainable Hateful Meme Detection

arXiv:2609.19778v1 Announce Type: new Abstract: Hateful memes spread abusive content through implicit interactions between images and text, posing serious threats to the safety of online communities.

Learning Reliable Parking Policies via Offline Reinforcement Learning with Quantized Action Representations

arXiv:2609.19894v1 Announce Type: new Abstract: Parking is a routine yet safety-critical task for autonomous vehicles operating in urban environments. However, cluttered and weakly structured parking

SAFARI: An Industrial Benchmark for LLM-Assisted Hazard Analysis and Risk Assessment

model-releasesarxiv-cs-cl

arXiv:2609.20584v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly considered for safety-critical engineering, yet their reliability in regulated functional-safety workflows

State-Change Learning for Prediction of Future Events in Endoscopic Videos

arXiv:2510.12904v2 Announce Type: replace Abstract: Surgical future prediction, driven by real-time AI analysis of surgical video, is critical for operating room safety and efficiency. It provides act

Beyond Direct Sensing: Harnessing Indirect Observations from Third-Party Sensors in Vehicle Tracking

arXiv:2609.18173v1 Announce Type: cross Abstract: Vehicle tracking is fundamental to applications ranging from urban mobility and public safety to security and defense. Conventional tracking relies on

17 Sept 2026

Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, n

17 Sept 2026

Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine

17 Sept 2026

Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge

arXiv:2609.16742v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference

Certified Uncertainty Propagation in One-Shot Federated Bayesian Models via Posterior Event Transport

model-releasesarxiv-cs-lg

arXiv:2609.16373v1 Announce Type: new Abstract: Probabilistic certification of Bayesian neural networks lower-bounds the posterior probability that a model satisfies a verifier-defined safety property

Efficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategy

arXiv:2609.16690v1 Announce Type: new Abstract: Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe n

GPEvac: GNN-Based PPO for Adaptive Evacuation Routing During Shooting Events

arXiv:2609.16163v1 Announce Type: new Abstract: The sharp increase in mass shootings underscores an urgent need for systems that guide victims to safety in real time. An effective evacuation system mu

RobResilience: Implementing and Evaluating a Resilience Framework for Cyber-Physical Embodied Systems

arXiv:2609.17349v1 Announce Type: cross Abstract: In embodied cyber-physical systems, active cyberattacks pose an immediate threat not just to data, but to physical integrity and human safety. While e

Robust Fault Detection in Mechanical Multimodal Time Series via Self-Supervised Cross-Modal Reconstruction

arXiv:2609.16314v1 Announce Type: new Abstract: Fault detection is essential in industrial systems, enabling early identification of abnormal behaviour and improving safety, reliability, and operation

Divide, Consult, Conquer: Capability Laundering Through Aligned LLMs

model-releasesarxiv-cs-ai

arXiv:2609.15383v1 Announce Type: cross Abstract: Language model safety is typically evaluated one interaction at a time. We show that a weaker, unaligned model can split a harmful task into benign-lo

From Refusal Tokens to Refusal Control: Discovering and Steering Category-Specific Refusal Directions

model-releasesarxiv-cs-ai

arXiv:2603.13359v2 Announce Type: replace Abstract: Language models are commonly fine-tuned for safety alignment to refuse harmful prompts. One approach fine-tunes them to generate categorical refusal

From Words to Wavelengths: VLMs for Few-Shot Multispectral Object Detection

arXiv:2512.15971v2 Announce Type: replace Abstract: Multispectral object detection is critical for safety-sensitive applications such as autonomous driving and surveillance, where robust perception un

How User-AI Mistreatment Occurs and Matters in Conversational Systems?

arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding

Inoculation Midtraining with Learned Neologisms

arXiv:2609.15886v1 Announce Type: new Abstract: Large language models (LLMs) often learn both desirable and undesirable properties during post-training. We study whether midtraining, an earlier traini

One Feedback System Does Not Fit All: Localising Data-to-Text Driver Coaching for the United Kingdom and Nigeria

arXiv:2609.14687v1 Announce Type: new Abstract: Data-to-text driver coaching is often presented as a generic pipeline from telematics events to advice. This paper argues that its content requires loca

Orientation Control of Soft Robots via Adiabatic Spectral Submanifolds

arXiv:2609.14376v1 Announce Type: new Abstract: Soft robots are commonly sought for safety-critical interactions in delicate environments, where accurate position and orientation control is imperative

Personalizing Personal Health Interfaces: Co-Design with Generative AI

arXiv:2609.15046v1 Announce Type: cross Abstract: Personal health interfaces present wellbeing data through standardized dashboards that rarely fit how people interpret or act on it. Personalizing the

Predictive audio representations for early detection and tracking of hidden dynamic objects

arXiv:2609.13595v1 Announce Type: cross Abstract: Predicting potential dangers is core to safety. Forecasting the presence of other traffic agents is core to danger prediction. Occluded traffic agents