LLMs in Interpreting Legal Documents
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Abstract (arXiv)
This chapter explores the application of Large Language Models in the legal domain, showcasing their potential to optimise and augment traditional legal tasks by analysing possible use cases, such as assisting in interpreting statutes, contracts, and case law, enhancing clarity in legal summarisation, contract negotiation, and information retrieval. There are several challenges that can arise from the application of such technologies, such as algorithmic monoculture, hallucinations, and compliance with existing regulations, including the EU's AI Act and recent U.S. initiatives, alongside the emerging approaches in China. Furthermore, two different benchmarks are presented.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 28 references that are in the map. First posted on arXiv 10 Dec 2025.
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References · 8
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
- 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,601
- 2023Towards Understanding Sycophancy in Language Modelscited by 1,040
- 2015A Neural Algorithm of Artistic Stylecited by 483
- 2023LawBench: Benchmarking Legal Knowledge of Large Language Modelscited by 117
- 2023Legal Extractive Summarization of U.S. Court Opinionscited by 9
- 2023Translating Legalese: Enhancing Public Understanding of Court Opinions with Legal Summarizerscited by 8
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