Min Yang

LLM agents achieve substantial performance gains by jointly learning credit at both the turn and token generation levels, overcoming limitations of existing single-level credit assignment methods.

Deterministic dependency graphs severely misalign with stochastic residual structures in decoupled diffusion forecasters, but dynamically sparsifying edges via residual uncertainty estimation eliminates redundant conditioning and repairs calibration.

An autonomous AI agent integrating Reasoning and Acting with Retrieval-Augmented Generation with Retrieval-Augmented Generation is developed to classify 10,211 Human Phenotype Ontology terms, enabling standardized panel design by providing reliable, automated classification supported by direct evidence.