21 citations · 69 across the 16 of their papers we have counts for
17 papers
Automatic Generation of Titles for Research Papers Using Language Models
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay
The title of a research paper conveys its primary idea and, occasionally, its conclusions in a clear and concise manner. Choosing an appropriate title is often challenging, and aut…
Overview of the SciHigh Track at FIRE 2025: Research Highlight Generation from Scientific Papers
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay
`SciHigh: Research Highlight Generation from Scientific Papers' focuses on the task of automatically generating concise, informative, and meaningful bullet-point highlights directl…
Comparative Analysis of Abstractive Summarization Models for Clinical Radiology Reports
Anindita Bhattacharya, Tohida Rehman, Debarshi Kumar Sanyal +1
The findings section of a radiology report is often detailed and lengthy, whereas the impression section is comparatively more compact and captures key diagnostic conclusions. This…
Evaluating LLMs and Pre-trained Models for Text Summarization Across Diverse Datasets
Tohida Rehman, Soumabha Ghosh, Kuntal Das +3
Text summarization plays a crucial role in natural language processing by condensing large volumes of text into concise and coherent summaries. As digital content continues to grow…
How Green are Neural Language Models? Analyzing Energy Consumption in Text Summarization Fine-tuning
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay
Artificial intelligence systems significantly impact the environment, particularly in natural language processing (NLP) tasks. These tasks often require extensive computational res…
Can pre-trained language models generate titles for research papers?
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay
The title of a research paper communicates in a succinct style the main theme and, sometimes, the findings of the paper. Coming up with the right title is often an arduous task, an…
Transfer Learning and Transformer Architecture for Financial Sentiment Analysis
Tohida Rehman, Raghubir Bose, Samiran Chattopadhyay +1
Financial sentiment analysis allows financial institutions like Banks and Insurance Companies to better manage the credit scoring of their customers in a better way. Financial doma…
Analysis of Multidomain Abstractive Summarization Using Salience Allocation
Tohida Rehman, Raghubir Bose, Soumik Dey +1
This paper explores the realm of abstractive text summarization through the lens of the SEASON (Salience Allocation as Guidance for Abstractive SummarizatiON) technique, a model de…
Automatic Recognition of Learning Resource Category in a Digital Library
Soumya Banerjee, Debarshi Kumar Sanyal, Samiran Chattopadhyay +2
Digital libraries often face the challenge of processing a large volume of diverse document types. The manual collection and tagging of metadata can be a time-consuming and error-p…
Generative AI for Software Metadata: Overview of the Information Retrieval in Software Engineering Track at FIRE 2023
Srijoni Majumdar, Soumen Paul, Debjyoti Paul +5
The Information Retrieval in Software Engineering (IRSE) track aims to develop solutions for automated evaluation of code comments in a machine learning framework based on human an…
An Evaluation of Non-Contrastive Self-Supervised Learning for Federated Medical Image Analysis
Soumitri Chattopadhyay, Soham Ganguly, Sreejit Chaudhury +2
Privacy and annotation bottlenecks are two major issues that profoundly affect the practicality of machine learning-based medical image analysis. Although significant progress has…
Exploring Self-Supervised Representation Learning For Low-Resource Medical Image Analysis
Soumitri Chattopadhyay, Soham Ganguly, Sreejit Chaudhury +2
The success of self-supervised learning (SSL) has mostly been attributed to the availability of unlabeled yet large-scale datasets. However, in a specialized domain such as medical…
An Analysis of Abstractive Text Summarization Using Pre-trained Models
Tohida Rehman, Suchandan Das, Debarshi Kumar Sanyal +1
People nowadays use search engines like Google, Yahoo, and Bing to find information on the Internet. Due to explosion in data, it is helpful for users if they are provided relevant…
Named Entity Recognition Based Automatic Generation of Research Highlights
Tohida Rehman, Debarshi Kumar Sanyal, Prasenjit Majumder +1
A scientific paper is traditionally prefaced by an abstract that summarizes the paper. Recently, research highlights that focus on the main findings of the paper have emerged as a…
Abstractive Text Summarization using Attentive GRU based Encoder-Decoder
Tohida Rehman, Suchandan Das, Debarshi Kumar Sanyal +1
In todays era huge volume of information exists everywhere. Therefore, it is very crucial to evaluate that information and extract useful, and often summarized, information out of…
Generation of Highlights from Research Papers Using Pointer-Generator Networks and SciBERT Embeddings
Tohida Rehman, Debarshi Kumar Sanyal, Samiran Chattopadhyay +2
Nowadays many research articles are prefaced with research highlights to summarize the main findings of the paper. Highlights not only help researchers precisely and quickly identi…
Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Data
Soumya Banerjee, Debarshi Kumar Sanyal, Samiran Chattopadhyay +2
The abstract of a scientific paper distills the contents of the paper into a short paragraph. In the biomedical literature, it is customary to structure an abstract into discourse…