Realizing the potential of near-term quantum computers to solve industry-relevant
constrained-optimization problems is a promising path to quantum advantage. In this work …

Automatic summarization of legal case judgements, which are known to be long and
complex, has traditionally been tried via extractive summarization models. In recent years …

Automatic summarization of legal case judgements has traditionally been attempted by
using extractive summarization methods. However, in recent years, abstractive …

Due to the lengthy and complex nature of legal documents, automatic summarization has
very high applicability in this domain. Recently, several researchers have proposed …

The appropriate understanding and fast processing of lengthy legal documents are
computationally challenging problems. Designing efficient automatic summarization …

Summarization of legal case judgement documents is a practical and challenging problem,
for which many summarization algorithms of different varieties have been tried. In this work …

Large-scale public datasets are vital for driving the progress of abstractive summarization,
especially in law, where documents have highly specialized jargon. However, the available …

Topic modeling techniques are popularly used for document clustering, large-scale text
analysis, information extraction from unstructured text documents, feature selection from …

Unlike the courts in western countries, public records of Indian judiciary are completely
unstructured and noisy. No large scale publicly available annotated datasets of Indian legal …

In the Legal AI field, the summarization of legal documents is very challenging. Since the
Indian case documents are much noisier and poorly organized, the summarization of legal …