A Survey of Legal Document Summarization Methods

Abstract: Legal document Summarization is one of the major applications of Artificial Intelligence for Law. This paper presents a survey of various types of approaches. Legal document summarization approaches are mainly categorized as: Extractive vs. Abstractive, Supervised vs. Unsupervised. Recently, Legal domain specific vs. General Domain Large Language Models for legal document summarization are developed. This paper also presents an overview of state-of-the-art technology using LLMs for Legal document summarization. An innovative approach of Knowledge Representation using Ripple-Down-Rules for document summarization is also presented. The paper also presents evaluation of methods.

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