7 papers · 1 filter
LexReward: A Taxonomy-Driven Reward Framework for Legal Language Models
Yida Cai, Xin Dai, Bingxiang He +5
Legal language models require reward signals that capture not only answer correctness but also the multidimensional quality of legal responses. Existing reward methods, however, of…
LexIssue: Benchmarking Legal Issue Identification in Chinese Civil Litigation
Huiyuan Xie, Yuqin Huang, Zhicheng Hao +4
Identifying the issues disputed between litigating parties is a crucial component of real-world litigation. However, legal issues remain comparatively underexplored in legal AI res…
LexKairos: Benchmarking Legal Temporal Capabilities in LLMs
Chenyang Li, Zejia Feng, Yuqin Huang +2
Large language models (LLMs) have demonstrated strong performance across a wide range of legal tasks. In legal practice, time is a critical concept that governs the validity of sta…
CLASE: A Hybrid Method for Chinese Legalese Stylistic Evaluation
Yiran Rex Ma, Yuxiao Ye, Huiyuan Xie
Legal text generated by large language models (LLMs) can usually achieve reasonable factual accuracy, but it frequently fails to adhere to the specialised stylistic norms and lingu…
LinguaGame: A Linguistically Grounded Game-Theoretic Paradigm for Multi-Agent Dialogue Generation
Yuxiao Ye, Yiming Zhang, Yiran Ma +3
Large Language Models (LLMs) have enabled Multi-Agent Systems (MASs) where agents interact through natural language to solve complex tasks or simulate multi-party dialogues. Recent…
LexRel: Benchmarking Legal Relation Extraction for Chinese Civil Cases
Yida Cai, Ranjuexiao Hu, Huiyuan Xie +6
Legal relations serve as an important analytical framework for dispute resolution in civil cases. However, legal relations in Chinese civil cases remain underexplored in the field…
LexChain: Modeling Legal Reasoning Chains for Chinese Tort Case Analysis
Huiyuan Xie, Chenyang Li, Huining Zhu +4
Legal reasoning is a fundamental component of legal analysis and decision-making. Existing computational approaches to legal reasoning predominantly rely on generic reasoning frame…