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4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems1 src1.3 Paper proposes evolving context parameterization for large language models1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions1 src4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems1 src1.3 Paper proposes evolving context parameterization for large language models1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions1 src
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papersSEP 11 04:00 UTC

Study Measures Reliability of Automated Jailbreak Evaluators

A new arXiv paper examines how well automated evaluators judge whether jailbreak attacks on language models succeed, noting that human expert review is expensive and hard to scale. The authors argue that jailbreak research often fails to properly validate the evaluators it depends on, and they empirically measure those evaluators' behavior.

papersSEP 10 04:00 UTC

Black-Box Red Teaming of Agentic AI: A Taxonomy-Driven Framework for Automated Risk Discovery

A new paper presents an automated black-box red teaming framework designed to uncover security risks in agentic AI systems. It uses a structured risk taxonomy to guide systematic testing, addressing the shortfalls of standard single-turn evaluations. The work targets agentic setups where models process untrusted inputs, invoke tools with real permissions, and act autonomously.