7 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…
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…
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…
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…