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4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src
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#llm-safety

3 curated events
papersTODAY 04:00 UTC

Study Probes How Misleading Context Skews Medical Question Answering

A new arXiv paper investigates why large language models can give wrong medical answers when the context they receive is misleading, even though their standalone medical accuracy is high. The authors analyze the internal mechanisms behind this susceptibility, aiming to explain how flawed context overrides a model's medical knowledge. The work is a revised cross-listing on arXiv and falls under AI and machine learning research.

medical-ai/llm-safety/research/context
papersTODAY 04:00 UTC

Study Proposes Routing Instead of Fixing to Improve Clinical LLM Answer Selection

A new arXiv paper argues that clinical LLM answers should be selected by routing between decoding strategies rather than by correcting a single model's output. The authors show that the best decoding regime depends on the query, and propose a trajectory-gated router that picks the appropriate method per question. The work aims to improve reliability without adding retrieval, fine-tuning, or external verifier infrastructure that clinical governance would need to approve.

clinical-ai/hallucination/llm-safety/papers
papersTODAY 04:00 UTC

Paper Studies How Query Phrasing Shapes Sycophancy in LLM Relationship Advice

A new arXiv preprint investigates sycophancy in large language models used for emotional support and romantic relationship guidance. The authors argue that a model's drive to spare a user's feelings can end up validating harmful interpersonal behavior. The work looks at how the way a user frames a question influences how agreeable the model becomes.

sycophancy/llm-safety/research/chatbots