Bhattacharyya, Pushpak

A multitask framework to detect depression, sentiment and multi-label emotion from suicide notes

Ghosh, S., Ekbal, A., & Bhattacharyya, P. (2022) · Cognitive Computation

Mental Health via WritingSentiment Analysis and Opinion Mining

Cited by 102

DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions

Ghosal, T., Verma, R., Ekbal, A., & Bhattacharyya, P. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Sentiment Analysis and Opinion MiningRecommender Systems and Techniques

Cited by 62

PUB: A Pragmatics Understanding Benchmark for Assessing LLMs’ Pragmatics Capabilities

Sravanthi, S., Doshi, M., Tankala, P., Murthy, R., Dabre, R., & Bhattacharyya, P. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 46

Why pay more? A simple and efficient named entity recognition system for tweets

Suman, C., Reddy, S. M., Saha, S., & Bhattacharyya, P. (2021) · Expert Systems with Applications

Topic ModelingMultimodal Machine Learning Applications

Cited by 27

Kitlm: Domain-specific knowledge integration into language models for question answering

Agarwal, A., Gawade, S., Azad, A. P., & Bhattacharyya, P. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

DocCGen: Document-based Controlled Code Generation

Pimparkhede, S., Kammakomati, M., Tamilselvam, S., Kumar, P., Kumar, A. P., & Bhattacharyya, P. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 1

Pretraining Language Models Using Translationese

Doshi, M., Dabre, R., & Bhattacharyya, P. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 1