The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Neural Legal Judgment Prediction in English
Open accessAbstract
Legal judgment prediction is the task of automatically predicting the outcome of a court case, given a text describing the case's facts.Previous work on using neural models for this task has focused on Chinese; only featurebased models (e.g., using bags of words and topics) have been considered in English.We release a new English legal judgment prediction dataset, containing cases from the European Court of Human Rights.We evaluate a broad variety of neural models on the new dataset, establishing strong baselines that surpass previous feature-based models in three tasks: (1) binary violation classification; (2) multi-label classification; (3) case importance prediction.We also explore if models are biased towards demographic information via data anonymization.As a side-product, we propose a hierarchical version of BERT, which bypasses BERT's length limitation.
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“Training Transformers with longer sequences with FlashAttention improves performance on the MIMIC-III [47] and ECtHR [6, 7] datasets.”
From FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness (2022) · cites this paper as [6]
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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On the Opportunities and Risks of Foundation Models
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv · doi:10.48550/arxiv.2108.07258 · Cited by 2,676
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
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“ECtHR contains legal cases from the European Court of Human Rights, each of which is mapped to articles of the Convention of Human Rights that were allegedly violaged.”
BackgroundMethodInfluentialLEGAL-BERT: The Muppets straight out of Law School
Chalkidis, I., Fergadiotis, M., Malakasiotis, P., Αλέτρας, Ν., & Androutsopoulos, I. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.261 · Cited by 1,453
Self-citationHow Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence
Zhong, H., Xiao, C., Tu, C., Zhang, T., Liu, Z., & Sun, M. (2020) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2020.acl-main.466 · Cited by 485
Lawformer: A pre-trained language model for Chinese legal long documents
Xiao, C., Hu, X., Liu, Z., Tu, C., & Sun, M. (2021) · AI Open · doi:10.1016/j.aiopen.2021.06.003 · Cited by 324
Metadata
- Authors
- Chalkidis, I., Androutsopoulos, I., & Aletras, N.
- Affiliations
- Athens University of Economics and Business (GR)
- Venue
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Published
- 2019
- Pages
- 4317-4323
- ISSN
- 0736-587X (ISSN-L)
- OpenAlex
- W2948586190
- Cited by
- 352
- References
- 26
- Citations by year
- 2026: 53 · 2025: 62 · 2024: 53 · 2023: 69 · 2022: 46 · 2021: 46 · 2020: 22 · 2019: 1
- FWCI
- 198.12
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Athens University of Economics and Business
- Topics
- Social Sciences › Law › Artificial Intelligence in Law
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
- Keywords
- legal judgment prediction, European Court of Human Rights, English legal texts, multi-label classification, demographic bias, data anonymization, neural language models
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