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Overview of CAIL2018: Legal Judgment Prediction Competition (1810.05851v1)

Published 13 Oct 2018 in cs.AI

Abstract: In this paper, we give an overview of the Legal Judgment Prediction (LJP) competition at Chinese AI and Law challenge (CAIL2018). This competition focuses on LJP which aims to predict the judgment results according to the given facts. Specifically, in CAIL2018 , we proposed three subtasks of LJP for the contestants, i.e., predicting relevant law articles, charges and prison terms given the fact descriptions. CAIL2018 has attracted several hundreds participants (601 teams, 1, 144 contestants from 269 organizations). In this paper, we provide a detailed overview of the task definition, related works, outstanding methods and competition results in CAIL2018.

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Authors (11)
  1. Haoxi Zhong (7 papers)
  2. Chaojun Xiao (39 papers)
  3. Zhipeng Guo (4 papers)
  4. Cunchao Tu (11 papers)
  5. Zhiyuan Liu (433 papers)
  6. Maosong Sun (337 papers)
  7. Yansong Feng (81 papers)
  8. Xianpei Han (103 papers)
  9. Zhen Hu (39 papers)
  10. Heng Wang (136 papers)
  11. Jianfeng Xu (13 papers)
Citations (30)

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