2024 TheUseofLLMsintheLegalFieldOpti
- (Mongoli, 2024) ⇒ Alessio Mongoli. (2024). “The Use of LLMs in the Legal Field: Optimizing Contract Management with Generative Artificial Intelligence..”
Subject Headings: Legal Document Analysis.
Notes
- The paper explores the integration of Large Language Models (LLMs) in the legal field, mainly focusing on optimizing contract management through Generative AI.
- The paper identifies challenges in legal document management, such as the time-intensive processes of contract drafting and analysis, and proposes an AI-driven solution to streamline these tasks.
- The paper provides a detailed summary of the evolution of Natural Language Processing (NLP) from rule-based systems to deep learning models, emphasizing the role of transformers in advancing NLP.
- The paper introduces Retrieval-Augmented Generation (RAG) as a method to enhance LLMs, combining information retrieval with generative capabilities to improve legal document analysis.
- The paper develops a proof of concept (POC) web application that uses LLMs to assist in generating and analyzing clauses, aiming to reduce the time legal professionals spend on these activities.
- The paper outlines the role of Orbyta Tech in the project, showcasing the company's expertise in IT consultancy and its contribution to the technological infrastructure of the proposed solution.
- The paper emphasizes the importance of prompt engineering in guiding LLMs to produce relevant and contextually accurate legal text, detailing strategies to optimize prompts for legal tasks.
- The paper addresses the limitations of LLMs, such as token constraints and the challenges in processing large legal documents, proposing document chunking as a viable solution.
- The paper compares different approaches, including RAG, fine-tuning, and prompt engineering, to optimize LLMs for legal applications, discussing the trade-offs and benefits of each.
- The paper concludes by highlighting the potential of generative AI in revolutionizing legal contract management and suggests future research directions to enhance system performance.
- The paper contributes to existing research by combining state-of-the-art AI techniques with practical legal applications, offering a novel approach to improving efficiency in legal processes.
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Abstract
In recent years, Artificial Intelligence (AI), including the emergence of ChatGPT, has attracted significant attention due to its increasing prevalence in several aspects of business processes. AI involves the development of automated systems capable of executing tasks traditionally performed by humans, with the aim of speeding up processes and reducing wasted time within organisations. This technology has also opened significant opportunities for application in the legal sector, traditionally engaged in analysing large amounts of documentation. This Master's thesis explores the use of Large Language Models (LLM) to support legal staff and reduce document management time. The aim of this research is to study, design, develop a POC (proof of concept) to address these challenges by implementing a web application where lawyers can analyse contracts e generate contract. The application is based on Retrieval-Augmented Generation (RAG) capable of providing fast, effective and high-quality responses. To achieve this goal, an in-depth analysis was conducted on large language models and the prompts used to guide them. To achieve this, the analyses focused on the effectiveness of LLMs in interpreting legal language and their ability to integrate information to produce relevant and coherent output. Particular attention was paid to the configuration of prompts and their optimisation to improve the accuracy of responses. In conclusion, this thesis highlights the considerable potential of generative AI in the legal field. By integrating the advantages of semantic embeddings for information retrieval with those of generative AI for producing answers, lawyers can significantly reduce the time spent in drafting new contracts, taking into account previous clauses, and analysing new contracts. This approach enables effective optimisation of legal processes, making contract management more efficient and accurate.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024 TheUseofLLMsintheLegalFieldOpti | Alessio Mongoli | The Use of LLMs in the Legal Field: Optimizing Contract Management with Generative Artificial Intelligence. | 2024 |