Publications

[Google Scholar] (* Equal Contribution)

Evaluating the Effectiveness of Large Language Models in Establishing Conversational Grounding
Biswesh Mohapatra, Manav Nitin Kapadnis, Laurent Romary, and Justine Cassell.
In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024).
[Paper] [arXiv]
SERPENT-VLM : Self-Refining Radiology Report Generation Using Vision Language Models
Manav Nitin Kapadnis, Sohan Patnaik, Abhilash Nandy, Sourjyadip Ray, Pawan Goyal, and Debdoot Sheet.
In Proceedings of the 6th Clinical Natural Language Processing Workshop at NAACL 2024.
[Paper] [arXiv]
***FastDoc***: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomy
Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik, Yash Parag Butala, Pawan Goyal, and Niloy Ganguly.
Transactions on Machine Learning Research (TMLR), 2024.
[Paper] [arXiv] [Code]

CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural Text
Abhilash Nandy, Manav Nitin Kapadnis, Pawan Goyal, and Niloy Ganguly.
In Findings of the Association for Computational Linguistics: EMNLP 2023.
[Paper] [arXiv] [Code]

Leveraging Pre-trained Language Models for Stance And Premise Classification
Millon Madhur Das, Archit Mangrulkar, Ishan Manchanda, Manav Nitin Kapadnis, and Sohan Patnaik.
In the 7th Social Media Mining for Health Applications (#SMM4H) workshop at COLING 2022.
[Paper] [Code]
An Evaluation Framework for Legal Document Summarization
Ankan Mullick, Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik, R Raghav, and Roshni Kar.
In the 13th Edition of its Language Resources and Evaluation Conference (LREC 2022).
[Paper] [arXiv] [Code]
Alzheimer’s disease detection using artificial intelligence
Abdulhamit Subasi, Manav Nitin Kapadnis, and Ayse Kosal Bulbul.
Book - Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence, 2022.
[Paper] [Code]
Fine-grained Intent Classification in the Legal Domain
Ankan Mullick*, Abhilash Nandy*, Manav Nitin Kapadnis*, Sohan Patnaik, and R Raghav.
In the Scientific Document Understanding workshop at Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022).
[Paper] [arXiv]

Leveraging Pre-trained Language Models for Key Point Matching
Manav Nitin Kapadnis*, Sohan Patnaik*, Siba Smarak Panigrahi*, Varun Madhavan*, and Abhilash Nandy.
In the 8th workshop on Argument Mining at Empirical Methods in Natural Language Processing (EMNLP 2021).
[Paper] [Code] [Poster]
CoCoTiNe : Compositional Committees of Tiny Networks
Goh Howe Seng, Tomas Maul, and Manav Nitin Kapadnis.
In the 28th International Conference on Neural Information Processing (ICONIP 2021).
[Paper] [Code]

CRScore++: Reinforcement Learning with Verifiable Tool and AI Feedback for Code Review
Manav Nitin Kapadnis, Atharva Naik, and Carolyn Rose.
arXiv preprint, 2025.
[arXiv]
PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics
Atharva Naik, Prakam, Darsh Agrawal, Yash Mathur, Manav Nitin Kapadnis, Yuwei An, Clayton Marr, Carolyn Rose, and David Mortensen.
arXiv preprint, 2025.
[arXiv]