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cs.CL2026

PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs

Yuting Huang, Yinghao Hu, Qian Xiao +7

Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challenging due to hallucinated lega…

cs.CL2025

ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation

Siying Zhou, Yiquan Wu, Hui Chen +6

Legal claims refer to the plaintiff's demands in a case and are essential to guiding judicial reasoning and case resolution. While many works have focused on improving the efficien…

cs.CL2025

Universal Legal Article Prediction via Tight Collaboration between Supervised Classification Model and LLM

Xiao Chi, Wenlin Zhong, Yiquan Wu +4

Legal Article Prediction (LAP) is a critical task in legal text classification, leveraging natural language processing (NLP) techniques to automatically predict relevant legal arti…

cs.CL2025

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios

Yuting Huang, Meitong Guo, Yiquan Wu +6

Recent advances in LegalAI have primarily focused on individual case judgment analysis, often overlooking the critical appellate process within the judicial system. Appeals serve a…

cs.CL2024

Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator

Chengyuan Liu, Shihang Wang, Lizhi Qing +4

Domain Large Language Models (LLMs) are developed for domain-specific tasks based on general LLMs. But it still requires professional knowledge to facilitate the expertise for some…

cs.CL2024

Gold Panning in Vocabulary: An Adaptive Method for Vocabulary Expansion of Domain-Specific LLMs

Chengyuan Liu, Shihang Wang, Lizhi Qing +4

While Large Language Models (LLMs) demonstrate impressive generation abilities, they frequently struggle when it comes to specialized domains due to their limited domain-specific k…