ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2406.14503
28
0

Overview of the CAIL 2023 Argument Mining Track

20 June 2024
Jingcong Liang
Junlong Wang
Xinyu Zhai
Yungui Zhuang
Yiyang Zheng
Xin Xu
Xiandong Ran
Xiaozheng Dong
Honghui Rong
Yanlun Liu
Hao Chen
Yuhan Wei
Donghai Li
Jiajie Peng
Xuanjing Huang
Chongde Shi
Yansong Feng
Yun Song
Zhongyu Wei
    ELM
    LRM
ArXivPDFHTML
Abstract

We give a detailed overview of the CAIL 2023 Argument Mining Track, one of the Chinese AI and Law Challenge (CAIL) 2023 tracks. The main goal of the track is to identify and extract interacting argument pairs in trial dialogs. It mainly uses summarized judgment documents but can also refer to trial recordings. The track consists of two stages, and we introduce the tasks designed for each stage; we also extend the data from previous events into a new dataset -- CAIL2023-ArgMine -- with annotated new cases from various causes of action. We outline several submissions that achieve the best results, including their methods for different stages. While all submissions rely on language models, they have incorporated strategies that may benefit future work in this field.

View on arXiv
Comments on this paper