Yiqun Liu

Despite high retrieval rates, LLMs miss over 47% of relevant studies in meta-analysis, exposing a critical gap in their systematic reasoning capabilities.

ReGrad enables scalable and reversible knowledge injection without the risk of catastrophic forgetting, outperforming traditional methods in both general and domain-specific tasks.

SKIM compresses procedural skills in LLMs by 30-60% without sacrificing performance, revolutionizing how we manage reusable natural language skills.

LexRubric reveals that even state-of-the-art LLMs struggle with open-ended legal tasks, exposing critical gaps in their contextual understanding and reasoning abilities.

Reliable civil court judgments can now be simulated with a framework that adapts to the complexities of legal claims and remedies.