Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization

Santosh T.y.s.s, Vatsal Venkatkrishna, Saptarshi Ghosh, Matthias Grabmair

Abstract
Legal professionals face the challenge of managing an overwhelming volume of lengthy judgments, making automated legal case summarization crucial. However, prior approaches mainly focused on training and evaluating these models within the same jurisdiction. In this study, we explore the cross-jurisdictional generalizability of legal case summarization models. Specifically, we explore how to effectively summarize legal cases of a target jurisdiction where reference summaries are not available. In particular, we investigate whether supplementing models with unlabeled target jurisdiction corpus and extractive silver summaries obtained from unsupervised algorithms on target data enhances transfer performance. Our comprehensive study on three datasets from different jurisdictions highlights the role of pre-training in improving transfer performance. We shed light on the pivotal influence of jurisdictional similarity in selecting optimal source datasets for effective transfer. Furthermore, our findings underscore that incorporating unlabeled target data yields improvements in general pre-trained models, with additional gains when silver summaries are introduced. This augmentation is especially valuable when dealing with extractive datasets and scenarios featuring limited alignment between source and target jurisdictions. Our study provides key insights for developing adaptable legal case summarization systems, transcending jurisdictional boundaries.
Anthology ID:
2024.naacl-long.231
Volume:
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Kevin Duh, Helena Gomez, Steven Bethard
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4136–4150
Language:
URL:
https://aclanthology.org/2024.naacl-long.231
DOI:
10.18653/v1/2024.naacl-long.231
Bibkey:
Cite (ACL):
Santosh T.y.s.s, Vatsal Venkatkrishna, Saptarshi Ghosh, and Matthias Grabmair. 2024. Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 4136–4150, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization (T.y.s.s et al., NAACL 2024)
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