LIVE PULSE
4.8 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 src2.1 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 Paper Examines How First Query Shapes Agentic Deep Search1 src1.3 Conformance-Driven Iterative Refinement for Natural-Language to SysMLv2 Translation1 src1.3 Neural Operators for Nonlinear Functionals on RKHS1 src4.8 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 src2.1 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 Paper Examines How First Query Shapes Agentic Deep Search1 src1.3 Conformance-Driven Iterative Refinement for Natural-Language to SysMLv2 Translation1 src1.3 Neural Operators for Nonlinear Functionals on RKHS1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE

SatIR

model1 events
papersTODAY 04:00 UTC

SatIR: High-Recall Constraint-Satisfaction Retrieval for Clinical Trial Matching

A new arXiv paper introduces SatIR, a retrieval method aimed at settings where candidates must meet a specific profile's constraints rather than just be topically similar. Clinical trial matching is used as the motivating high-stakes case, where missing an eligible patient or trial carries real cost. The approach targets scalable, high-recall constraint satisfaction across many competing profiles.