DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Yue, Shengbin, Chen, Wei, Wang, Siyuan, Li, Bingxuan, Shen, Chenchen, Liu, Shujun, Zhou, Yuxuan, Xiao, Yao, Yun, Song, Huang, Xuanjing, Wei, Zhongyu

arXiv.org Artificial Intelligence 

We propose DISC-LawLLM, an intelligent legal system utilizing large language models (LLMs) to provide a wide range of legal services. We adopt legal syllogism prompting strategies to construct supervised fine-tuning datasets in the Chinese Judicial domain and fine-tune LLMs with legal reasoning capability. We augment LLMs with a retrieval module to enhance models' ability to access and utilize external legal knowledge. A comprehensive legal benchmark, DISC-Law-Eval, is presented to evaluate intelligent legal systems from both objective and subjective dimensions. Quantitative and qualitative results on DISC-Law-Eval demonstrate the effectiveness of our system in serving various users across diverse legal scenarios. The detailed resources are available at https://github.com/FudanDISC/DISC-LawLLM.

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