Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

5-2022

Abstract

Lawsandtheirinterpretations, legal arguments and agreements are typically expressed in writing, leading to the production of vast corpora of legal text. Their analysis, which is at the center of legal practice, becomes increasingly elaborate as these collections grow in size. Natural language understanding (NLU) technologies can be a valuable tool to support legal practitioners in these endeavors. Their usefulness, however, largely depends on whether current state-of-the-art models can generalize across various tasks in the legal domain. To answer this currently open question, we introduce the Legal General Language Understanding Evaluation (LexGLUE) benchmark, a collection of datasets for evaluating model performance across a diverse set of legal NLU tasks in a standardized way. We also provide an evaluation and analysis of several generic and legal-oriented models demonstrating that the latter consistently offer performance improvements across multiple tasks.

Discipline

Artificial Intelligence and Robotics | Science and Technology Law

Research Areas

Innovation, Technology and the Law

Publication

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, Dublin, Ireland, 2022 May 22-27

Volume

1

First Page

4310

Last Page

4330

ISBN

9781955917216

Identifier

10.18653/v1/2022.acl-long.297

Publisher

ACL

City or Country

Dublin

Additional URL

https://aclanthology.org/2022.acl-long.297

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