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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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ai-research-agents

topic2 events
papersSEP 10 04:00 UTC

RAP benchmark probes how LLM research agents track shifting scientific attention

Researchers introduced RAP, a task for measuring whether large language models serving as research agents can follow changes in scholarly attention, which has been hard to assess because reviews and proposed ideas lack verifiable outcomes. The findings indicate that these models acquire evidence in ways that are biased toward the specific target they are given.

papersSEP 10 04:00 UTC

Researchers Propose Discovery Certification Protocol for Auditing AI Research Agents

An arXiv paper argues that benchmark scores by themselves are not sufficient evidence that AI research agents have made genuine scientific discoveries. The authors introduce the Discovery Certification Protocol, which converts an agent's claimed results into executable recovery and feedback tests that can be independently run. The first of its gates checks that reported results can actually be reproduced from the recorded evidence.