Yiquan Wu

Ensuring fairness in social survey simulation is critical, as biased outputs can misrepresent underrepresented groups. This issue is growing as large language models (LLMs) are increasingly used for this task. However, standard fine-tuning based on Empirical Risk Minimization (ERM) often under-op...

Artificial intelligence has become increasingly prevalent in the legal domain. However, LegalAI systems often struggle with vague user queries that lack essential legal details, leading to suboptimal performance in practical applications. To address this challenge, we propose FactFiller, a novel...

Large language models have demonstrated strong performance on general-purpose tasks but often fail to satisfy the accuracy requirements of knowledge-intensive domains such as law, medicine, and finance. Complex domain-specific generation is inherently compositional, involving multiple atomic skil...