short-paper

Summarizing Legal Regulatory Documents using Transformers

Authors:

Kaweh Djafari Naini,

Ismail Sengor Altingovde,

Juan Bernabé-Moreno,

Enrique Herrera-ViedmaAuthors Info & Claims

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 2426 - 2430

https://doi.org/10.1145/3477495.3531872

Published: 07 July 2022 Publication History

Abstract

Companies invest a substantial amount of time and resources in ensuring the compliance to the existing regulations or in the form of fines when compliance cannot be proven in auditing procedures. The topic is not only relevant, but also highly complex, given the frequency of changes and amendments, the complexity of the cases and the difficulty of the juristic language. This paper aims at applying advanced extractive summarization to democratize the understanding of regulations, so that non-jurists can decide which regulations deserve further follow-up. To achieve that, we first create a corpus named EUR-LexSum EUR-LexSum containing 4595 curated European regulatory documents and their corresponding summaries. We then fine-tune transformer-based models which, applied to this corpus, yield a superior performance (in terms of ROUGE metrics) compared to a traditional extractive summarization baseline. Our experiments reveal that even with limited amounts of data such transformer-based models are effective in the field of legal document summarization.

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References

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Digital Library

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Cited By

Siino MFalco MCroce DRosso P(2025)Exploring LLMs Applications in Law: A Literature Review on Current Legal NLP ApproachesIEEE Access10.1109/ACCESS.2025.353321713(18253-18276)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3533217
Sebastian RBoratto LGena CMarras MGermanakos PPopescus E(2024)Adaptive Search Support for Teachers in Lesson PlanningAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664921(20-24)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3664921
Malik MZhao ZFonseca MRao SCohen SHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)CivilSum: A Dataset for Abstractive Summarization of Indian Court DecisionsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657859(2241-2250)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657859
Show More Cited By

Index Terms

Summarizing Legal Regulatory Documents using Transformers
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction
  2. Machine learning
    1. Machine learning approaches
      1. Neural networks

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cover image ACM Conferences

SIGIR '22: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2022

3569 pages

ISBN:9781450387323

DOI:10.1145/3477495

General Chairs:
Enrique Amigo
UNED
,
Pablo Castells
UAM and Amazon
,
Julio Gonzalo
UNED
,
Program Chairs:
Ben Carterette
Spotify
,
J. Shane Culpepper
RMIT University
,
Gabriella Kazai
Waseda University

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGIR: ACM Special Interest Group on Information Retrieval

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New York, NY, United States

Publication History

Published: 07 July 2022

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SIGIR

SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

July 11 - 15, 2022

Madrid, Spain

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Siino MFalco MCroce DRosso P(2025)Exploring LLMs Applications in Law: A Literature Review on Current Legal NLP ApproachesIEEE Access10.1109/ACCESS.2025.353321713(18253-18276)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3533217
Sebastian RBoratto LGena CMarras MGermanakos PPopescus E(2024)Adaptive Search Support for Teachers in Lesson PlanningAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664921(20-24)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3631700.3664921
Malik MZhao ZFonseca MRao SCohen SHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)CivilSum: A Dataset for Abstractive Summarization of Indian Court DecisionsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657859(2241-2250)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657859
Harasta JNovotná TSavelka J(2024)It cannot be right if it was written by AI: on lawyers’ preferences of documents perceived as authored by an LLM vs a humanArtificial Intelligence and Law10.1007/s10506-024-09422-wOnline publication date: 3-Dec-2024
https://doi.org/10.1007/s10506-024-09422-w
Dadas SKozłowski MPoświata RPerełkiewicz MBiałas MGrębowiec M(2024)A support system for the detection of abusive clauses in B2C contractsArtificial Intelligence and Law10.1007/s10506-024-09408-8Online publication date: 26-Jun-2024
https://doi.org/10.1007/s10506-024-09408-8
Prabhakar PPati P(2024)Extractive Summarization of Indian Legal Judgments: Bridging NLP and Generative AI for Socially Responsible Content GenerationGenerative AI: Current Trends and Applications10.1007/978-981-97-8460-8_15(329-352)Online publication date: 10-Dec-2024
https://doi.org/10.1007/978-981-97-8460-8_15
Albayati MFındık O(2024)Turkish Legal Single-Document SummarizingInformation Technologies and Their Applications10.1007/978-3-031-73420-5_3(32-41)Online publication date: 17-Oct-2024
https://doi.org/10.1007/978-3-031-73420-5_3
Greco C(2024)Advancing Legal NLP: Application of Pre-trained Language Models in the Legal DomainNew Trends in Database and Information Systems10.1007/978-3-031-70421-5_26(309-317)Online publication date: 14-Nov-2024
https://doi.org/10.1007/978-3-031-70421-5_26
Rahali AAkhloufi M(2023)End-to-End Transformer-Based Models in Textual-Based NLPAI10.3390/ai40100044:1(54-110)Online publication date: 5-Jan-2023
https://doi.org/10.3390/ai4010004
Wei YLiu XMa YWang XNie LChua TChen HDuh WHuang HKato MMothe JPoblete B(2023)Strategy-aware Bundle Recommender SystemProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591771(1198-1207)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591771
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