activity
20232026
most citedApplicability of Large Language Models and Generative Models for Legal Case Judgement Summarization

3 citations · 6 across the 12 of their papers we have counts for

collaborators

12 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.LG2025★ 1 cited

RSTGCN: Railway-centric Spatio-Temporal Graph Convolutional Network for Train Delay Prediction

Koyena Chowdhury, Paramita Koley, Abhijnan Chakraborty +1

Accurate prediction of train delays is critical for efficient railway operations. While earlier approaches have largely focused on forecasting the exact delays of individual trains…

cs.AI2025

Judging by Appearances? Auditing and Intervening Vision-Language Models for Bail Prediction

Sagnik Basu, Shubham Prakash, Ashish Maruti Barge +4

Large language models (LLMs) have been extensively used for legal judgment prediction tasks based on case reports and crime history. However, with a surge in the availability of la…

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.CY2024

Sponsored is the New Organic: Implications of Sponsored Results on Quality of Search Results in the Amazon Marketplace

Abhisek Dash, Saptarshi Ghosh, Animesh Mukherjee +2

Interleaving sponsored results (advertisements) amongst organic results on search engine result pages (SERP) has become a common practice across multiple digital platforms. Adverti…

cs.CV2024

Breaking the Global North Stereotype: A Global South-centric Benchmark Dataset for Auditing and Mitigating Biases in Facial Recognition Systems

Siddharth D Jaiswal, Animesh Ganai, Abhisek Dash +2

Facial Recognition Systems (FRSs) are being developed and deployed globally at unprecedented rates. Most platforms are designed in a limited set of countries but deployed in worldw…

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.CY2024

Auditing the Grid-Based Placement of Private Label Products on E-commerce Search Result Pages

Siddharth D Jaiswal, Abhisek Dash, Nitika Shroff +3

E-commerce platforms support the needs and livelihoods of their two most important stakeholders -- customers and producers/sellers. Multiple algorithmic systems, like ``search'' sy…

cs.CY2024

Investigating Nudges toward Related Sellers on E-commerce Marketplaces: A Case Study on Amazon

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +2

E-commerce marketplaces provide business opportunities to millions of sellers worldwide. Some of these sellers have special relationships with the marketplace by virtue of using th…

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.CY2024

Antitrust, Amazon, and Algorithmic Auditing

Abhisek Dash, Abhijnan Chakraborty, Saptarshi Ghosh +4

In digital markets, antitrust law and special regulations aim to ensure that markets remain competitive despite the dominating role that digital platforms play today in everyone's…

cs.CL2023★ 1 cited

Prompted Zero-Shot Multi-label Classification of Factual Incorrectness in Machine-Generated Summaries

Aniket Deroy, Subhankar Maity, Saptarshi Ghosh

This study addresses the critical issue of factual inaccuracies in machine-generated text summaries, an increasingly prevalent issue in information dissemination. Recognizing the p…