Author

Ying-Ming Pu

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#machine learning Preprint Oct 2026

Triage-PiEvo: Evidence Admission for Principle-Evolving Scientific Agents

Large language model (LLM)-based AI Scientists advance scientific discovery, yet they suffer from inefficiencies due to noisy observations. Existing principle-evolving agents act on every anomaly, leaving its source unresolved: a new mechanism or an evaluation artifact, so invalid revisions bias evolution. To address t...

Pei-Ze Li, Ying-Ming Pu, Xing-Guo Xu et al. · 0 citations

#machine learning Preprint Sep 2026

Collaborative Principle Evolution via Evidence Transfer for Scientific Discovery

COEVOLVE enables branches to collaborate through shared measurements while keeping their principle posteriors separate, and establishes when evidence sharing accelerates parallel discovery and when transfer safeguards are necessary to limit negative or inert transfers.

Ying-Ming Pu, Hong-Yu Chen, Tao Lin · 0 citations