This paper reviews research on automatic summarising in the last decade. This work has
grown, stimulated by technology and by evaluation programmes. The paper uses several …

Abstract Argumentation represents the study of views and opinions that humans express
with the goal of reaching a conclusion through logical reasoning. Since the 1950's, several …

Enormous amount of online information, available in legal domain, has made legal text
processing an important area of research. In this paper, we attempt to survey different text …

Summarization of legal case judgments is an important problem because the huge length
and complexity of such documents make them difficult to read as a whole. Many …

The standard approach for abstractive text summarization is to use an encoder-decoder
architecture. The encoder is responsible for capturing the general meaning from the source …

We report on a pilot experiment in automatic, extractive summarization of legal cases
concerning Post-traumatic Stress Disorder from the US Board of Veterans' Appeals. We …

Argument mining, a subfield of natural language processing and text mining, is a process of
extracting argumentative text portions and identifying the role the selected texts play. Legal …

In this paper we describe our method for the summarization of legal documents hel** a
legal expert determine the key ideas of a judgment. Our approach is based on the …

In this paper, we treat sentence annotation as a classification task. We employ sequence-to-
sequence models to take sentence position information into account in identifying case law …

This paper presents our work on the development of a new methodology for automatic
summarization of justice decision. We describe LetSum (Legal text Summarizer), a prototype …