#user-modeling

LIVE PULSE

5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.8 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src

2 curated events

papersTODAY 04:00 UTC

Mind2Dialogue Framework Trains Language Models to Model User Mental States

A new arXiv paper introduces Mind2Dialogue, a method that trains language models to be more aware of the people they interact with by simulating users' mental states during training. The authors frame the problem as a supervision gap: models need signals about human internal states, which are rarely available in standard dialogue data. The approach targets long-term collaboration in learning, reasoning, and decision-making tasks.

llm/dialogue/user-modeling/training

papersSEP 10 04:00 UTC

New arXiv paper explores co-creating life goals from everyday computer use

A preprint cross-listed in arXiv's AI and computational linguistics categories examines how software could infer what a person is ultimately trying to achieve based on their routine computer activity. Leveraging recent progress in user modeling, the authors describe an approach in which AI systems and users jointly articulate life goals rather than the machine simply automating individual tasks. The v2 announcement indicates a revised version of the paper.

user-modeling/human-ai-interaction/research