Research outputs
2026
Early detection of anorexia from reddit posts using time series based transformer model
Saini, S., & Sen, P. (2026). Early detection of anorexia from reddit posts using time series based transformer model. Discover Computing, 29(1). doi:10.1007/s10791-026-09903-3
A Counterfactual Explanation Framework for Retrieval Models
A case study for automated attribute extraction from legal documents using large language models
Adhikary, S., Sen, P., Roy, D., & Ghosh, K. (2026). A case study for automated attribute extraction from legal documents using large language models. Artificial Intelligence and Law, 34(1), 245-266. doi:10.1007/s10506-024-09425-7
2025
FEC-Real: Enhancing Financial Time Series Task with a Hybrid Encoder
Zhang, Z., Sen, P., Chen, T., Jiang, Z., & Su, J. (2025). FEC-Real: Enhancing Financial Time Series Task with a Hybrid Encoder. In 2025 IEEE International Conference on Big Data (BigData) (pp. 1-10). IEEE. doi:10.1109/bigdata66926.2025.11401576
Report on the 3rd Symposium on NLP for Social Good (NSG 2025)
Sen, P., Saha, T., & Bollegala, D. (2025). Report on the 3rd Symposium on NLP for Social Good (NSG 2025). ACM SIGIR Forum, 59(2), 1-10. doi:10.1145/3799914.3799925
From Posts to Patterns: Early Detection of Anorexia on Reddit
Dissecting Bias in LLMs: A Mechanistic Interpretability Perspective
Unraveling the Influence of Training Data and Internal Structures in Large Language Models for Enhanced Explainability (Student Abstract)
Li, L., & Sen, P. (2025). Unraveling the Influence of Training Data and Internal Structures in Large Language Models for Enhanced Explainability (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 39(28), 29407-29409. doi:10.1609/aaai.v39i28.35268
Adaptive Retrieval-Augmented Generation for Conversational Systems
Wang, X., Sen, P., Li, R., & Yilmaz, E. (2025). Adaptive Retrieval-Augmented Generation for Conversational Systems. In Findings of the Association for Computational Linguistics: NAACL 2025 (pp. 491-503). Association for Computational Linguistics. doi:10.18653/v1/2025.findings-naacl.30
Dissecting Bias in LLMs: Perspective A Mechanistic Interpretability
Bashir, Z., Chandna, B., & Sen, P. (2025). Dissecting Bias in LLMs: Perspective A Mechanistic Interpretability. Transactions on Machine Learning Research, 2025-December.
Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks
Tucat, M., Mukherjee, A., Sen, P., Sun, M., & Rivasplata, O. (2025). Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks. Transactions on Machine Learning Research, 2025-June.
2024
CROWD: Certified Robustness via Weight Distribution for Smoothed Classifiers against Backdoor Attack
Sun, S., Sen, P., & Ruan, W. (2024). CROWD: Certified Robustness via Weight Distribution for Smoothed Classifiers against Backdoor Attack. In Findings of the Association for Computational Linguistics: EMNLP 2024 (pp. 17056-17070). Association for Computational Linguistics. doi:10.18653/v1/2024.findings-emnlp.993
FinBPM: A Framework for Portfolio Management-based Financial Investor Behavior Perception Model
Zhang, Z., Sen, P., Wang, Z., Sun, R., Jiang, Z., & Su, J. (2024). FinBPM: A Framework for Portfolio Management-based Financial Investor Behavior Perception Model. In Eacl 2024 18th Conference of the European Chapter of the Association for Computational Linguistics Proceedings of the Conference Vol. 1 (pp. 246-257).
Knowledge Base-enhanced Multilingual Relation Extraction with Large Language Models
Chen, T., Sen, P., Wang, Z., Jiang, Z., & Su, J. (2024). Knowledge Base-enhanced Multilingual Relation Extraction with Large Language Models. In Ceur Workshop Proceedings Vol. 3818 (pp. 47-58).
Preface
Sen, P., Saha, T., & Bollegala, D. (2024). Preface. Ceur Workshop Proceedings, 3764.
Report on the 1st Symposium on NLP for Social: Good (NSG 2023)
Sen, P., Saha, T., & Bollegala, D. (2023). Report on the 1st Symposium on NLP for Social: Good (NSG 2023). ACM SIGIR Forum, 57(2), 1-9. doi:10.1145/3642979.3642989
Report on the 2nd Symposium on NLP for Social Good.
Sen, P., Saha, T., & Bollegala, D. (2024). Report on the 2nd Symposium on NLP for Social Good.. In P. Sen, T. Saha, & D. Bollegala (Eds.), NSG Vol. 3764. CEUR-WS.org. Retrieved from https://ceur-ws.org/Vol-3764
Simulated Task Oriented Dialogues for Developing Versatile Conversational Agents
Wang, X., Sen, P., Li, R., & Yilmaz, E. (2024). Simulated Task Oriented Dialogues for Developing Versatile Conversational Agents. In Unknown Book (Vol. 14608, pp. 157-172). doi:10.1007/978-3-031-56027-9_10
2023
Explainability of Text Processing and Retrieval Methods
Anand, A., Saha, S., Sen, P., & Mitra, M. (2023). Explainability of Text Processing and Retrieval Methods. In Proceedings of the 15th Annual Meeting of the Forum for Information Retrieval Evaluation (pp. 153-157). ACM. doi:10.1145/3632754.3632944
Automated Attribute Extraction from Legal Proceedings
Automated Argument Generation from Legal Facts
Explainable Information Retrieval
Anand, A., Sen, P., Saha, S., Verma, M., & Mitra, M. (2023). Explainable Information Retrieval. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 3448-3451). ACM. doi:10.1145/3539618.3594249
Task2KB: A Public Task-Oriented Knowledge Base
Sen, P., Wang, X., Xu, R., & Yilmaz, E. (2023). Task2KB: A Public Task-Oriented Knowledge Base. In Proceedings of the AAAI Conference on Artificial Intelligence Vol. 37 (pp. 16482-16484). Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v37i13.27086
Task2KB: A Public Task-Oriented Knowledge Base
A Word Sense Distribution-based approach for Semantic Change Prediction
Tang, X., Zhou, Y., Aida, T., Sen, P., & Bollegala, D. (2023). A Word Sense Distribution-based approach for Semantic Change Prediction. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 3575-3590). Association for Computational Linguistics. doi:10.18653/v1/2023.findings-emnlp.231
Can Word Sense Distribution Detect Semantic Changes of Words?
Tang, X., Zhou, Y., Aida, T., Sen, P., & Bollegala, D. (2023). Can Word Sense Distribution Detect Semantic Changes of Words?. In FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS - EMNLP 2023 (pp. 3575-3590). Retrieved from https://www.webofscience.com/
Finding Important Arguments from a Legal Case
Konstantynowicz, D., Wojciechowski, F. G., & Sen, P. (2023). Finding Important Arguments from a Legal Case. In Ceur Workshop Proceedings Vol. 3614 (pp. 33-37).
Lexical Entrainment for Conversational Systems
Shi, Z., Sen, P., & Lipani, A. (2023). Lexical Entrainment for Conversational Systems. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 278-293). Association for Computational Linguistics. doi:10.18653/v1/2023.findings-emnlp.22
2022
Measuring and Comparing the Consistency of IR Models for Query Pairs with Similar and Different Information Needs
Sen, P., Saha, S., Ganguly, D., Verma, M., & Roy, D. (2022). Measuring and Comparing the Consistency of IR Models for Query Pairs with Similar and Different Information Needs. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 4449-4453). ACM. doi:10.1145/3511808.3557637
Workshop on Proactive and Agent-Supported Information Retrieval (PASIR)
Jones, G. J. F., Sen, P., Ganguly, D., & Yilmaz, E. (2022). Workshop on Proactive and Agent-Supported Information Retrieval (PASIR). In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (pp. 5167-5168). ACM. doi:10.1145/3511808.3557939
I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts
Sen, P., Ganguly, D., & Jones, G. J. F. (2022). I Know What You Need: Investigating Document Retrieval Effectiveness with Partial Session Contexts. ACM Transactions on Information Systems, 40(3), 1-30. doi:10.1145/3488667
2021
Proactive information retrieval
Sen, P. (2021). Proactive information retrieval. ACM SIGIR Forum, 55(2), 1-2. doi:10.1145/3527546.3527576
2020
The Curious Case of IR Explainability: Explaining Document Scores within and across Ranking Models
Sen, P., Ganguly, D., Verma, M., & Jones, G. J. F. (2020). The Curious Case of IR Explainability: Explaining Document Scores within and across Ranking Models. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2069-2072). ACM. doi:10.1145/3397271.3401286
Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning
Sen, P., & Ganguly, D. (2020). Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 34(03), 2685-2692. doi:10.1609/aaai.v34i03.5654
2019
Word-
Sen, P., Ganguly, D., & Jones, G. (2019). Word-. In Proceedings of the 2019 Conference of the North (pp. 1041-1051). Association for Computational Linguistics. doi:10.18653/v1/n19-1109
2018
Procrastination is the Thief of Time
Sen, P., Ganguly, D., & Jones, G. (2018). Procrastination is the Thief of Time. In The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval (pp. 1157-1160). ACM. doi:10.1145/3209978.3210114
Evaluation of Personalised Information Retrieval at CLEF 2018 (PIR-CLEF)
Pasi, G., Jones, G. J. F., Curtis, K., Marrara, S., Sanvitto, C., Ganguly, D., & Sen, P. (2018). Evaluation of Personalised Information Retrieval at CLEF 2018 (PIR-CLEF). In Lecture Notes in Computer Science (pp. 335-342). Springer International Publishing. doi:10.1007/978-3-319-98932-7_29
Tempo-Lexical Context Driven Word Embedding for Cross-Session Search Task Extraction
Sen, P., Ganguly, D., & Jones, G. (2018). Tempo-Lexical Context Driven Word Embedding for Cross-Session Search Task Extraction. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (pp. 283-292). Association for Computational Linguistics. doi:10.18653/v1/n18-1026
2017
Overview of the CLEF 2017 Personalised Information Retrieval Pilot Lab (PIR-CLEF 2017)
Pasi, G., Jones, G. J. F., Marrara, S., Sanvitto, C., Ganguly, D., & Sen, P. (2017). Overview of the CLEF 2017 Personalised Information Retrieval Pilot Lab (PIR-CLEF 2017). In Lecture Notes in Computer Science (pp. 338-345). Springer International Publishing. doi:10.1007/978-3-319-65813-1_29
2016
Joint Estimation of Topics and Hashtag Relevance in Cross-Lingual Tweets
Sen, P., Ganguly, D., & Jones, G. J. F. (2016). Joint Estimation of Topics and Hashtag Relevance in Cross-Lingual Tweets. In Proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval (pp. 291-294). ACM. doi:10.1145/2970398.2970425