collaborators

5 papers

cs.CL2026

Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process

Zhijun Chen, Zeyu Ji, Qianren Mao +12

We propose LLM-PeerReview, an unsupervised LLM Ensemble method that selects the most ideal response from multiple LLM-generated candidates for each query, harnessing the collective…

cs.CL2026

LexGenius: An Expert-Level Benchmark for Large Language Models in Legal General Intelligence

Wenjin Liu, Haoran Luo, Xin Feng +6

Legal general intelligence (GI) refers to artificial intelligence (AI) that encompasses legal understanding, reasoning, and decision-making, simulating the expertise of legal exper…

cs.CL2025

LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load

Theo Guidroz, Diego Ardila, Jimmy Li +24

Information on the web, such as scientific publications and Wikipedia, often surpasses users' reading level. To help address this, we used a self-refinement approach to develop a L…

cs.CL2025

JurisCTC: Enhancing Legal Judgment Prediction via Cross-Domain Transfer and Contrastive Learning

Zhaolu Kang, Hongtian Cai, Xiangyang Ji +2

In recent years, Unsupervised Domain Adaptation (UDA) has gained significant attention in the field of Natural Language Processing (NLP) owing to its ability to enhance model gener…

cs.LG2025

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations

Kaixuan Huang, Jiacheng Guo, Zihao Li +15

Large language models have demonstrated impressive performance on challenging mathematical reasoning tasks, which has triggered the discussion of whether the performance is achieve…