LLMs in Interpreting Legal Documents

Simone Corbo
12/10/2025
cs.CLcs.AI

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey

94% match2024

Large Language Models Meet Legal Artificial Intelligence: A Survey

93% match1 repo202025

LLM Agents in Law: Taxonomy, Applications, and Challenges

92% match2026

Evaluating the Role of Large Language Models in Legal Practice in India

91% match2025

Legal Evalutions and Challenges of Large Language Models

91% match2024

Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directions

90% match2026

Cite this paper

@article{corbo2025llms,
  title  = {LLMs in Interpreting Legal Documents},
  author = {Simone Corbo},
  year   = {2025},
  eprint = {2512.09830},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.09830v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2512.09830.svg)](https://codeofpaper.com/paper/2512.09830)

Discussion