28 citations · 63 across the 12 of their papers we have counts for
12 papers
Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers
Vasudha Bhatnagar, Purnima Bindal, Vikas Kumar +1
Zero-shot summarization using Large Language Models (LLMs) has significantly advanced the abstractive summarization task by producing coherent and fluent summaries. However, underl…
PRecG: Legal Precedent Retrieval with Graph Neural Networks and Rhetorical Role Segmentation
Devanshu Verma, Vasudha Bhatnagar, Vikas Kumar +1
Legal precedent retrieval is a fundamental task in legal case preparation, planning, litigation strategy, and legal research. Current approaches for automatic precedent retrieval m…
AugAbEx: Bridging Abstractive and Extractive Legal Summarization
Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar
Automatic summarization of legal judgments liberates law professionals from heavy cognitive burden due to the complexity of the language, context-sensitive legal jargon, and the le…
Citation-Based Summarization of Landmark Judgments
Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar +2
Landmark judgments are of prime importance in the Common Law System because of their exceptional jurisprudence and frequent references in other judgments. In this work, we leverage…
Human Centered AI for Indian Legal Text Analytics
Sudipto Ghosh, Devanshu Verma, Balaji Ganesan +3
Legal research is a crucial task in the practice of law. It requires intense human effort and intellectual prudence to research a legal case and prepare arguments. Recent boom in g…
Infusing Knowledge into Large Language Models with Contextual Prompts
Kinshuk Vasisht, Balaji Ganesan, Vikas Kumar +1
Knowledge infusion is a promising method for enhancing Large Language Models for domain-specific NLP tasks rather than pre-training models over large data from scratch. These augme…
Deep dive into language traits of AI-generated Abstracts
Vikas Kumar, Amisha Bharti, Devanshu Verma +1
Generative language models, such as ChatGPT, have garnered attention for their ability to generate human-like writing in various fields, including academic research. The rapid prol…
Personalized Summarization of Scientific Scholarly Texts
Alka Khurana, Vasudha Bhatnagar, Vikas Kumar
In this paper, we present a proposal for an unsupervised algorithm, P-Summ, that generates an extractive summary of scientific scholarly text to meet the personal knowledge needs o…
Quantitative Discourse Cohesion Analysis of Scientific Scholarly Texts using Multilayer Networks
Vasudha Bhatnagar, Swagata Duari, S. K. Gupta
Discourse cohesion facilitates text comprehension and helps the reader form a coherent narrative. In this study, we aim to computationally analyze the discourse cohesion in scienti…
Investigating Entropy for Extractive Document Summarization
Alka Khurana, Vasudha Bhatnagar
Automatic text summarization aims to cut down readers time and cognitive effort by reducing the content of a text document without compromising on its essence. Ergo, informativenes…
Similar Cases Recommendation using Legal Knowledge Graphs
Jaspreet Singh Dhani, Ruchika Bhatt, Balaji Ganesan +2
A legal knowledge graph constructed from court cases, judgments, laws and other legal documents can enable a number of applications like question answering, document similarity, an…
An Overview of the Commercial Cloud Monitoring Tools: Research Dimensions, Design Issues, and State-of-the-Art
Khalid Alhamazani, Rajiv Ranjan, Karan Mitra +4
Cloud monitoring activity involves dynamically tracking the Quality of Service (QoS) parameters related to virtualized resources (e.g., VM, storage, network, appliances, etc.), the…