activity
20172026
most citedHow Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?

24 citations · 95 across the 22 of their papers we have counts for

collaborators

22 papers

cs.CL2026

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh

In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditional extractive and abstractive…

cs.CL2025

MARRO: Multi-headed Attention for Rhetorical Role Labeling in Legal Documents

Purbid Bambroo, Subinay Adhikary, Paheli Bhattacharya +3

Identification of rhetorical roles like facts, arguments, and final judgments is central to understanding a legal case document and can lend power to other downstream tasks like le…

cs.CL2024★ 3 cited

Applicability of Large Language Models and Generative Models for Legal Case Judgement Summarization

Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh

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, generat…

cs.AI2024★ 1 cited

Artificial Intelligence (AI) in Legal Data Mining

Aniket Deroy, Naksatra Kumar Bailung, Kripabandhu Ghosh +2

Despite the availability of vast amounts of data, legal data is often unstructured, making it difficult even for law practitioners to ingest and comprehend the same. It is importan…

cs.CL2023★ 10 cited

Nonet at SemEval-2023 Task 6: Methodologies for Legal Evaluation

Shubham Kumar Nigam, Aniket Deroy, Noel Shallum +6

This paper describes our submission to the SemEval-2023 for Task 6 on LegalEval: Understanding Legal Texts. Our submission concentrated on three subtasks: Legal Named Entity Recogn…

cs.CV2023

Exemplar-Free Continual Transformer with Convolutions

Anurag Roy, Vinay Kumar Verma, Sravan Voonna +3

Continual Learning (CL) involves training a machine learning model in a sequential manner to learn new information while retaining previously learned tasks without the presence of…

cs.CL2023★ 24 cited

How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?

Aniket Deroy, Kripabandhu Ghosh, Saptarshi Ghosh

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

cs.CL2022★ 13 cited

Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation

Abhay Shukla, Paheli Bhattacharya, Soham Poddar +4

Summarization of legal case judgement documents is a challenging problem in Legal NLP. However, not much analyses exist on how different families of summarization models (e.g., ext…

cs.IR2022★ 1 cited

Legal Case Document Similarity: You Need Both Network and Text

Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal +1

Estimating the similarity between two legal case documents is an important and challenging problem, having various downstream applications such as prior-case retrieval and citation…

cs.CL2021

Incorporating Domain Knowledge for Extractive Summarization of Legal Case Documents

Paheli Bhattacharya, Soham Poddar, Koustav Rudra +2

Automatic summarization of legal case documents is an important and practical challenge. Apart from many domain-independent text summarization algorithms that can be used for this…

cs.CL2021

ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation

Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam +4

An automated system that could assist a judge in predicting the outcome of a case would help expedite the judicial process. For such a system to be practically useful, predictions…

cs.IR2021

Fairness for Whom? Understanding the Reader's Perception of Fairness in Text Summarization

Anurag Shandilya, Abhisek Dash, Abhijnan Chakraborty +2

With the surge in user-generated textual information, there has been a recent increase in the use of summarization algorithms for providing an overview of the extensive content. Tr…

cs.IR2021

An Unsupervised Normalization Algorithm for Noisy Text: A Case Study for Information Retrieval and Stance Detection

Anurag Roy, Shalmoli Ghosh, Kripabandhu Ghosh +1

A large fraction of textual data available today contains various types of 'noise', such as OCR noise in digitized documents, noise due to informal writing style of users on microb…

cs.SI2020

Utilizing Microblogs for Assisting Post-Disaster Relief Operations via Matching Resource Needs and Availabilities

Ritam Dutt, Moumita Basu, Kripabandhu Ghosh +1

During a disaster event, two types of information that are especially useful for coordinating relief operations are needs and availabilities of resources (e.g., food, water, medici…

cs.IR2020

Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity

Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal +1

Computing similarity between two legal case documents is an important and challenging task in Legal IR, for which text-based and network-based measures have been proposed in litera…

cs.CV2020

ZSCRGAN: A GAN-based Expectation Maximization Model for Zero-Shot Retrieval of Images from Textual Descriptions

Anurag Roy, Vinay Kumar Verma, Kripabandhu Ghosh +1

Most existing algorithms for cross-modal Information Retrieval are based on a supervised train-test setup, where a model learns to align the mode of the query (e.g., text) to the m…

cs.SI2020★ 5 cited

NARMADA: Need and Available Resource Managing Assistant for Disasters and Adversities

Kaustubh Hiware, Ritam Dutt, Sayan Sinha +3

Although a lot of research has been done on utilising Online Social Media during disasters, there exists no system for a specific task that is critical in a post-disaster scenario…

cs.SI2020★ 13 cited

Methods for Computing Legal Document Similarity: A Comparative Study

Paheli Bhattacharya, Kripabandhu Ghosh, Arindam Pal +1

Computing similarity between two legal documents is an important and challenging task in the domain of Legal Information Retrieval. Finding similar legal documents has many applica…

cs.IR2019★ 11 cited

Identification of Rhetorical Roles of Sentences in Indian Legal Judgments

Paheli Bhattacharya, Shounak Paul, Kripabandhu Ghosh +2

Automatically understanding the rhetorical roles of sentences in a legal case judgement is an important problem to solve, since it can help in several downstream tasks like summari…

cs.IR2018

Summarizing User-generated Textual Content: Motivation and Methods for Fairness in Algorithmic Summaries

Abhisek Dash, Anurag Shandilya, Arindam Biswas +3

As the amount of user-generated textual content grows rapidly, text summarization algorithms are increasingly being used to provide users a quick overview of the information conten…

cs.IR2018

Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora

Mitodru Niyogi, Kripabandhu Ghosh, Arnab Bhattacharya

Cross-lingual information retrieval is a challenging task in the absence of aligned parallel corpora. In this paper, we address this problem by considering topically aligned corpor…

cs.IR2017★ 14 cited

Microblog Retrieval for Post-Disaster Relief: Applying and Comparing Neural IR Models

Prannay Khosla, Moumita Basu, Kripabandhu Ghosh +1

Microblogging sites like Twitter and Weibo have emerged as important sourcesof real-time information on ongoing events, including socio-political events, emergency events, and so o…