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

Shengbin Yue, Wei Chen, Siyuan Wang, Bingxuan Li, Chenchen Shen +6 more
9/20/2023
cs.CL

Official code: FudanDISC/DISC-LawLLM (933 stars, Apache-2.0, last commit 2025-05-27).

Abstract

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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Code Implementations(1)

FudanDISC/DISC-LawLLMOfficial100%
Apache-2.0

[中文法律大模型] DISC-LawLLM: an intelligent legal system powered by large language models (LLMs) to provide a wide range of legal services.

93393PythonSep 21, 20231 years agoApache-2.0
domain-llmlegal-intelligencelegal-llmnlp

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Cite this paper

@article{yue2023disclawllm,
  title  = {DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services},
  author = {Shengbin Yue and Wei Chen and Siyuan Wang and Bingxuan Li and Chenchen Shen and Shujun Liu and Yuxuan Zhou and Yao Xiao and Song Yun and Xuanjing Huang and Zhongyu Wei},
  year   = {2023},
  eprint = {2309.11325},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.11325v2}
}

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