AI Safety news and analysis on Web Pulse: 22706 curated articles tracking the latest AI Safety developments, tools, and research, updated continuously from vetted sources.
OPAQUE, a confidential computing company that runs AI workloads inside hardware-isolated environments, released an open standard called Weight Custody Manifest that lets AI model builders decide when and where their weig…
A new arXiv paper (2609.05461v1) introduces ARC-Bench, a no-leak, fixed-candidate protocol that finds frozen JEPA-style world models rank candidate actions incorrectly, with the top-scored candidate almost always subopti…
A new arXiv paper introduces SWORD (Systematic Wikidata-based Object-Relation Distortion), a benchmark that tests whether large language models consistently reject factually incorrect statements across eight widely spoke…
A study posted to arXiv (2609.09363v1) found only a weak context-memory conflict in large language models, with counterfactual RDF triple inputs scoring just 0.05 lower on a 1-5 faithfulness scale than factual inputs whe…
Snowflake AI Research introduced HybridDeepResearch, a benchmark of 380 tool-dependent tasks that require agents to combine web search and SQL against LiveSQLBench-Base-Lite databases and public web corpora. Evaluations …
Google Gemini 3.0 Pro recovered only 2.8% of a 180-contaminant answer key when auditing large batches of documents, down from 50% on single documents and 60% on small batches, according to an arXiv paper (2609.09696v1) t…
A new arXiv paper (2609.05437v1) introduces NormReact, a dataset of 450 hand-annotated norm violation scenarios, to evaluate second-order social reasoning — metanorms — in large language models. Across six models, the re…
A World Values Survey-grounded simulation of LLM agent societies found that more than 50% of personas fail to express their assigned WVS value profiles from the outset, while only 2-7% drift after repeated conversations,…
Researchers proposed TEAM-Design, a rule that assigns every task two replay probabilities — one per baseline — to decide under a fixed replay budget whether a human-AI workflow should be kept over the human alone or the …
Researchers proposed NOMAD-RL (Neural Online Meta-Adaptation for Dynamics), a general-purpose reinforcement learning controller that transfers across heterogeneous thermal zones through a universal, non-invasive thermost…
A study of vision-language model reliability found that a frozen Qwen2.5-VL-3B-Instruct model showed an evidence monotonicity violation rate (EMVR) of 0.436, with 92.0% of 176 accepted GQA-derived trajectories containing…
A new arXiv paper (2609.09528v1) introduces MotionBlind, a contrastive benchmark showing that Video-LLMs cannot reliably judge physically grounded motion, with open models sitting near the 6.25% chance floor and scale pr…
Researchers introduced VANTAGE-Bench, a benchmark measuring an "Infrastructure AI Gap" in Vision-Language Models (VLMs) that rely on fixed cameras for open-loop tasks such as safety monitoring and operational logging. Ev…
A study of seven experiments on live shared LLM-serving systems found that KV-cache timing side-channel reliability collapses under multi-tenant contention, with mean Cohen's d on a vLLM server running DeepSeek-R1-Distil…
A study evaluating fourteen LLMs found that tool-using agents overtrust unreliable tool returns, with mean adoption of corrupted content exceeding one third for every tool and reaching 68.0% for web search. The research,…
A black-box attack called AgentLeak can clone a stronger proprietary LLM agent's task-solving capabilities onto a weaker attacker-controlled agent, improving task pass rates by over 40% versus direct skill reuse and reco…
A new arXiv paper (2609.05800v1) reports that naive activation steering of large language models causes substantial spillover, where the effect intended for one value leaks into others, and traces the problem to geometri…
A new benchmark called ABLE, introduced in arXiv paper 2609.05818v1, evaluates how well LLM agents use biological AI models such as ProteinMPNN and AlphaFold3 in dual-use protein design workflows. Testing 15 frontier mod…
A paper posted to arXiv (2609.05894v1) argues that the traditional scaling paradigms behind modern AI systems are hitting friction that prevents continued exponential growth, citing peak data limitations, rising computat…
A new arXiv paper (2609.06391v1) proposes an assurance-by-construction blueprint for graph-agentic retrieval-augmented generation systems used in social-good settings, built around five interface contracts covering evide…