A Paper Accepted at ACL 2022

24 February 2022, by Özge Sevgili Ergüven

The ‘60th Annual Meeting of the Association for Computational Linguistics (2022)’ accepted the following paper:

• LexGLUE: A Benchmark Dataset for Legal Language Understanding in English, Ilias Chalkidis (University of Copenhagen), Abhik Jana (Universität Hamburg), Dirk Hartung (Bucerius Law School - Center for Legal Technology and Data Science), Michael James Bommarito (Michigan State College of Law), Ion Androutsopoulos (Athens University of Economics and Business), Daniel Martin Katz (Illinois Tech - Chicago Kent College of Law), Nikolaos Aletras (University of Sheffield)

Abstract: Law, interpretations of law, legal arguments, agreements, etc. 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.

The paper will be soon available in our "Publications" section.