collaborators

10 papers

cs.AI2026

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens

Chengshuai Zhao, Zhen Tan, Pingchuan Ma +5

Chain-of-Thought (CoT) prompting has been shown to be effective in eliciting structured reasoning (i.e., CoT reasoning) from large language models (LLMs). Regardless of its popular…

cs.CL2026

DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models

Yuxuan Jiang, Dawei Li, Francis Ferraro

While Large Reasoning Models (LRMs) have demonstrated success in complex reasoning tasks through long chain-of-thought (CoT) reasoning, their inference often involves excessively v…

cs.LG2026

Preference Leakage: A Contamination Problem in LLM-as-a-judge

Dawei Li, Renliang Sun, Yue Huang +6

Large Language Models (LLMs) as judges and LLM-based data synthesis have emerged as two fundamental LLM-driven data annotation methods in model development. While their combination…

cs.AI2025

From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge

Dawei Li, Bohan Jiang, Liangjie Huang +10

Assessment and evaluation have long been critical challenges in artificial intelligence (AI) and natural language processing (NLP). Traditional methods, usually matching-based or s…

cs.AI2025

Leveraging Social Determinants of Health in Alzheimer's Research Using LLM-Augmented Literature Mining and Knowledge Graphs

Tianqi Shang, Shu Yang, Weiqing He +7

Growing evidence suggests that social determinants of health (SDoH), a set of nonmedical factors, affect individuals' risks of developing Alzheimer's disease (AD) and related demen…

cs.LG2025

Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models

Joseph Lee, Shu Yang, Jae Young Baik +8

Predicting phenotypes with complex genetic bases based on a small, interpretable set of variant features remains a challenging task. Conventionally, data-driven approaches are util…