# Zero-shot Transfer of Article-aware Legal Outcome Classification for European Court of Human Rights Cases

arXiv: https://arxiv.org/abs/2302.00609 · HTML: https://mlsanity.com/paper/2302.00609/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 36 of its 71 references that are in the map.
- First posted on arXiv 1 Feb 2023.

## Builds on (most cited first, 30 of 36)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Domain-Adversarial Training of Neural Networks](https://mlsanity.com/paper/1505.07818/) (2015)
- [Unsupervised Domain Adaptation by Backpropagation](https://mlsanity.com/paper/1409.7495/) (2014)
- [LexGLUE: A Benchmark Dataset for Legal Language Understanding in English](https://mlsanity.com/paper/2110.00976/) (2021)
- [Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://mlsanity.com/paper/1909.00161/) (2019)
- [Neural Legal Judgment Prediction in English](https://mlsanity.com/paper/1906.02059/) (2019)
- [When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset](https://mlsanity.com/paper/2104.08671/) (2021)
- [Enhanced LSTM for Natural Language Inference](https://mlsanity.com/paper/1609.06038/) (2016)
- [Neural Unsupervised Domain Adaptation in NLP---A Survey](https://mlsanity.com/paper/2006.00632/) (2020)
- [LEGAL-BERT: The Muppets straight out of Law School](https://mlsanity.com/paper/2010.02559/) (2020)
- [Stance Detection with Bidirectional Conditional Encoding](https://mlsanity.com/paper/1606.05464/) (2016)
- [ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation](https://mlsanity.com/paper/2105.13562/) (2021)
- [Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases](https://mlsanity.com/paper/2103.13084/) (2021)
- [Reasoning about Entailment with Neural Attention](https://mlsanity.com/paper/1509.06664/) (2015)
- [A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering](https://mlsanity.com/paper/2005.05257/) (2020)
- [Learning to Predict Charges for Criminal Cases with Legal Basis](https://mlsanity.com/paper/1707.09168/) (2017)
- [PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains](https://mlsanity.com/paper/2102.12206/) (2021)
- [Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark](https://mlsanity.com/paper/2110.00806/) (2021)
- [Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network](https://mlsanity.com/paper/1905.03969/) (2019)
- [FairLex: A Multilingual Benchmark for Evaluating Fairness in Legal Text Processing](https://mlsanity.com/paper/2203.07228/) (2022)
- [Revisiting Transformer-based Models for Long Document Classification](https://mlsanity.com/paper/2204.06683/) (2022)
- [Strong Baselines for Neural Semi-supervised Learning under Domain Shift](https://mlsanity.com/paper/1804.09530/) (2018)
- [An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification](https://mlsanity.com/paper/2210.05529/) (2022)
- [Exploring the Use of Text Classification in the Legal Domain](https://mlsanity.com/paper/1710.09306/) (2017)
- [Predicting the Law Area and Decisions of French Supreme Court Cases](https://mlsanity.com/paper/1708.01681/) (2017)
- [Adversarial Domain Adaptation for Duplicate Question Detection](https://mlsanity.com/paper/1809.02255/) (2018)
- [Deep Contextualized Self-training for Low Resource Dependency Parsing](https://mlsanity.com/paper/1911.04286/) (2019)
- [Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts](https://mlsanity.com/paper/2210.13836/) (2022)
- [Robust Multilingual Part-of-Speech Tagging via Adversarial Training](https://mlsanity.com/paper/1711.04903/) (2017)

## Built on by (most cited first, 14 of 14)

- [ChronosLex: Time-aware Incremental Training for Temporal Generalization of Legal Classification Tasks](https://mlsanity.com/paper/2405.14211/) (2024)
- [Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification](https://mlsanity.com/paper/2402.07214/) (2024)
- [LexAbSumm: Aspect-based Summarization of Legal Decisions](https://mlsanity.com/paper/2404.00594/) (2024)
- [Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization](https://mlsanity.com/paper/2403.19317/) (2024)
- [Towards Explainability and Fairness in Swiss Judgement Prediction: Benchmarking on a Multilingual Dataset](https://mlsanity.com/paper/2402.17013/) (2024)
- [Towards Explainability in Legal Outcome Prediction Models](https://mlsanity.com/paper/2403.16852/) (2024)
- [Query-driven Relevant Paragraph Extraction from Legal Judgments](https://mlsanity.com/paper/2404.00595/) (2024)
- [Incorporating Precedents for Legal Judgement Prediction on European Court of Human Rights Cases](https://mlsanity.com/paper/2409.18644/) (2024)
- [The Craft of Selective Prediction: Towards Reliable Case Outcome Classification -- An Empirical Study on European Court of Human Rights Cases](https://mlsanity.com/paper/2409.18645/) (2024)
- [Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning](https://mlsanity.com/paper/2606.27069/) (2026)
- [VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights](https://mlsanity.com/paper/2310.11368/) (2023)
- [ECtHR-PCR: A Dataset for Precedent Understanding and Prior Case Retrieval in the European Court of Human Rights](https://mlsanity.com/paper/2404.00596/) (2024)
- [Towards Supporting Legal Argumentation with NLP: Is More Data Really All You Need?](https://mlsanity.com/paper/2406.10974/) (2024)
- [Hybrid Deep Learning for Legal Text Analysis: Predicting Punishment Durations in Indonesian Court Rulings](https://mlsanity.com/paper/2410.20104/) (2024)

## Abstract (arXiv)

In this paper, we cast Legal Judgment Prediction on European Court of Human Rights cases into an article-aware classification task, where the case outcome is classified from a combined input of case facts and convention articles. This configuration facilitates the model learning some legal reasoning ability in mapping article text to specific case fact text. It also provides an opportunity to evaluate the model's ability to generalize to zero-shot settings when asked to classify the case outcome with respect to articles not seen during training. We devise zero-shot experiments and apply domain adaptation methods based on domain discrimination and Wasserstein distance. Our results demonstrate that the article-aware architecture outperforms straightforward fact classification. We also find that domain adaptation methods improve zero-shot transfer performance, with article relatedness and encoder pre-training influencing the effect.