4 papers
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…
GARL: Game-Theoretic Reinforcement Learning for Multi-Agent Strategic Prioritisation
Yuxiao Ye, Yiwen Zhang, Huiyuan Xie +2
LLM-based multi-agent systems are increasingly used for strategic decision-making tasks. In such settings, performance depends not only on individual model capabilities, but also o…
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…