# Overview of CAIL2018: Legal Judgment Prediction Competition

arXiv: https://arxiv.org/abs/1810.05851 · HTML: https://mlsanity.com/paper/1810.05851/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Oct 2018.

## Built on by (most cited first, 13 of 13)

- [A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges](https://mlsanity.com/paper/2204.04859/) (2022)
- [Legal Syllogism Prompting: Teaching Large Language Models for Legal Judgment Prediction](https://mlsanity.com/paper/2307.08321/) (2023)
- [Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models](https://mlsanity.com/paper/2407.08440/) (2024)
- [STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionals](https://mlsanity.com/paper/2406.15313/) (2024)
- [Debate-Feedback: A Multi-Agent Framework for Efficient Legal Judgment Prediction](https://mlsanity.com/paper/2504.05358/) (2025)
- [Bilingual BSARD: Extending Statutory Article Retrieval to Dutch](https://mlsanity.com/paper/2412.07462/) (2024)
- [RAG+: Enhancing Retrieval-Augmented Generation with Application-Aware Reasoning](https://mlsanity.com/paper/2506.11555/) (2025)
- [Athena: Retrieval-augmented Legal Judgment Prediction with Large Language Models](https://mlsanity.com/paper/2410.11195/) (2024)
- [The Cases LJP Never Sees: Prosecution Decision Prediction for More Complete Criminal Liability Assessment](https://mlsanity.com/paper/2605.28464/) (2026)
- [LegalWorld: A Life-Cycle Interactive Environment for Legal Agents](https://mlsanity.com/paper/2606.18728/) (2026)
- [An Empirical Investigation of Domain Adaptation Ability for Chinese Spelling Check Models](https://mlsanity.com/paper/2401.14630/) (2024)
- [Overview of the CAIL 2023 Argument Mining Track](https://mlsanity.com/paper/2406.14503/) (2024)
- [JusticeAxis: Benchmarking Legal Judgment between Rigid Rule Application and Ungrounded Discretion](https://mlsanity.com/paper/2610.00353/) (2026)

## Abstract (arXiv)

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.