Yi Shen

Compact and reliable prediction sets can be achieved in healthcare AI even with limited labeled data, thanks to a novel integration of conformal risk minimization and optimal transport.

Token-oriented inference optimizations can cut production costs and boost efficiency, transforming large model services from merely callable to fully operable.

HiMPO assigns less-entangled credit to memory updates, significantly boosting long-horizon agent performance while minimizing blame leakage from errors.