# Automatic Judgment Prediction via Legal Reading Comprehension

arXiv: https://arxiv.org/abs/1809.06537 · HTML: https://mlsanity.com/paper/1809.06537/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Sep 2018.

## Built on by (most cited first, 19 of 19)

- [ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation](https://mlsanity.com/paper/2105.13562/) (2021)
- [Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark](https://mlsanity.com/paper/2110.00806/) (2021)
- [A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges](https://mlsanity.com/paper/2204.04859/) (2022)
- [Legal Judgment Prediction with Multi-Stage CaseRepresentation Learning in the Real Court Setting](https://mlsanity.com/paper/2107.05192/) (2021)
- [ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the US](https://mlsanity.com/paper/2211.00582/) (2022)
- [U-CREAT: Unsupervised Case Retrieval using Events extrAcTion](https://mlsanity.com/paper/2307.05260/) (2023)
- [Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts](https://mlsanity.com/paper/2406.04136/) (2024)
- [Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/2112.06370/) (2021)
- [SemEval 2023 Task 6: LegalEval - Understanding Legal Texts](https://mlsanity.com/paper/2304.09548/) (2023)
- [Unsupervised Law Article Mining based on Deep Pre-Trained Language Representation Models with Application to the Italian Civil Code](https://mlsanity.com/paper/2112.03033/) (2021)
- [Japanese Tort-case Dataset for Rationale-supported Legal Judgment Prediction](https://mlsanity.com/paper/2312.00480/) (2023)
- [Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction](https://mlsanity.com/paper/2409.07055/) (2024)
- [Unsupervised Simplification of Legal Texts](https://mlsanity.com/paper/2209.00557/) (2022)
- [Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-view](https://mlsanity.com/paper/2305.02558/) (2023)
- [ALJP: An Arabic Legal Judgment Prediction in Personal Status Cases Using Machine Learning Models](https://mlsanity.com/paper/2309.00238/) (2023)
- [Exploring Graph Neural Networks for Indian Legal Judgment Prediction](https://mlsanity.com/paper/2310.12800/) (2023)
- [JurisCTC: Enhancing Legal Judgment Prediction via Cross-Domain Transfer and Contrastive Learning](https://mlsanity.com/paper/2504.17264/) (2025)
- [ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation](https://mlsanity.com/paper/2508.17234/) (2025)
- [Entity Graph Extraction from Legal Acts -- a Prototype for a Use Case in Policy Design Analysis](https://mlsanity.com/paper/2209.00944/) (2022)

## Abstract (arXiv)

Automatic judgment prediction aims to predict the judicial results based on case materials. It has been studied for several decades mainly by lawyers and judges, considered as a novel and prospective application of artificial intelligence techniques in the legal field. Most existing methods follow the text classification framework, which fails to model the complex interactions among complementary case materials. To address this issue, we formalize the task as Legal Reading Comprehension according to the legal scenario. Following the working protocol of human judges, LRC predicts the final judgment results based on three types of information, including fact description, plaintiffs' pleas, and law articles. Moreover, we propose a novel LRC model, AutoJudge, which captures the complex semantic interactions among facts, pleas, and laws. In experiments, we construct a real-world civil case dataset for LRC. Experimental results on this dataset demonstrate that our model achieves significant improvement over state-of-the-art models. We will publish all source codes and datasets of this work on urlgithub.com for further research.