Large language models in law: A survey

被引:1
|
作者
Lai, Jinqi [1 ]
Gan, Wensheng [1 ]
Wu, Jiayang [1 ]
Qi, Zhenlian [2 ]
Yu, Philip S. [3 ]
机构
[1] Jinan Univ, Guangzhou 510632, Peoples R China
[2] Guangdong Ecoengn Polytech, Guangzhou 510520, Peoples R China
[3] Univ Illinois, Chicago, IL USA
来源
AI OPEN | 2024年 / 5卷
基金
中国国家自然科学基金;
关键词
Artificial intelligence; LLMs; Justice; Legal model; ARTIFICIAL-INTELLIGENCE; AI; JUSTICE; ACCESS; COURTS; RISK;
D O I
10.1016/j.aiopen.2024.09.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The advent of artificial intelligence (AI) has significantly impacted the traditional judicial industry. Moreover, recently, with the development of AI-generated content (AIGC), AI and law have found applications in various domains, including image recognition, automatic text generation, and interactive chat. With the rapid emergence and growing popularity of large models, it is evident that AI will drive transformation in the traditional judicial industry. However, the application of legal large language models (LLMs) is still in its nascent stage. Several challenges need to be addressed. In this paper, we aim to provide a comprehensive survey of legal LLMs. We not only conduct an extensive survey of LLMs but also expose their applications in the judicial system. We first provide an overview of AI technologies in the legal field and showcase the recent research in LLMs. Then, we discuss the practical implementations presented by legal LLMs, such as providing legal advice to users and assisting judges during trials. In addition, we explore the limitations of legal LLMs, including data, algorithms, and judicial practice. Finally, we summarize practical recommendations and propose future development directions to address these challenges.
引用
收藏
页码:181 / 196
页数:16
相关论文
共 50 条
  • [1] Large Language Models in Finance: A Survey
    Li, Yinheng
    Wang, Shaofei
    Ding, Han
    Chen, Hang
    PROCEEDINGS OF THE 4TH ACM INTERNATIONAL CONFERENCE ON AI IN FINANCE, ICAIF 2023, 2023, : 374 - 382
  • [2] Explainability for Large Language Models: A Survey
    Zhao, Haiyan
    Chen, Hanjie
    Yang, Fan
    Liu, Ninghao
    Deng, Huiqi
    Cai, Hengyi
    Wang, Shuaiqiang
    Yin, Dawei
    Du, Mengnan
    ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2024, 15 (02)
  • [3] A survey on multimodal large language models
    Yin, Shukang
    Fu, Chaoyou
    Zhao, Sirui
    Li, Ke
    Sun, Xing
    Xu, Tong
    Chen, Enhong
    NATIONAL SCIENCE REVIEW, 2024, 11 (12)
  • [4] A survey of multilingual large language models
    Qin, Libo
    Chen, Qiguang
    Zhou, Yuhang
    Chen, Zhi
    Li, Yinghui
    Liao, Lizi
    Li, Min
    Che, Wanxiang
    Yu, Philip S.
    PATTERNS, 2025, 6 (01):
  • [5] A survey on LoRA of large language models
    Mao, Yuren
    Ge, Yuhang
    Fan, Yijiang
    Xu, Wenyi
    Mi, Yu
    Hu, Zhonghao
    Gao, Yunjun
    FRONTIERS OF COMPUTER SCIENCE, 2025, 19 (07)
  • [6] A survey on large language models for recommendation
    Wu, Likang
    Zheng, Zhi
    Qiu, Zhaopeng
    Wang, Hao
    Gu, Hongchao
    Shen, Tingjia
    Qin, Chuan
    Zhu, Chen
    Zhu, Hengshu
    Liu, Qi
    Xiong, Hui
    Chen, Enhong
    WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2024, 27 (05):
  • [7] A survey on multimodal large language models
    Shukang Yin
    Chaoyou Fu
    Sirui Zhao
    Ke Li
    Xing Sun
    Tong Xu
    Enhong Chen
    National Science Review, 2024, 11 (12) : 277 - 296
  • [8] Large language models for medicine: a survey
    Zheng, Yanxin
    Gan, Wensheng
    Chen, Zefeng
    Qi, Zhenlian
    Liang, Qian
    Yu, Philip S.
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2025, 16 (02) : 1015 - 1040
  • [9] A Survey on Evaluation of Large Language Models
    Chang, Yupeng
    Wang, Xu
    Wang, Jindong
    Wu, Yuan
    Yang, Linyi
    Zhu, Kaijie
    Chen, Hao
    Yi, Xiaoyuan
    Wang, Cunxiang
    Wang, Yidong
    Ye, Wei
    Zhang, Yue
    Chang, Yi
    Yu, Philip S.
    Yang, Qiang
    Xie, Xing
    ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2024, 15 (03)
  • [10] A comprehensive survey of large language models and multimodal large models in medicine
    Xiao, Hanguang
    Zhou, Feizhong
    Liu, Xingyue
    Liu, Tianqi
    Li, Zhipeng
    Liu, Xin
    Huang, Xiaoxuan
    INFORMATION FUSION, 2025, 117