[1] Tripto, N. I., Venkatraman, S., Nahar, M., & Lee. D. (2025). Beyond checkmate: exploring the creative chokepoints in AI text, In The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP) (Accepted). [paper link]
[2] Lucas, J. S., Chen, J., Al-Lawati, A., Nahar, M., & Mehrabani, M. (2025). Chain-of-Interactions: iterative ICL framework for abstractive task-oriented dialogue summarization of conversational AI interactions. In Findings of the Association for Computational Linguistics (EMNLP) (Accepted).
[3] Nahar, M., Lee, E. J., Park, J. W., & Lee, D. (2025). Catch me if you search: when contextual web search results affect the detection of hallucinations. Computers in Human Behavior 173, 108763 (online version). [paper link]
[4] Nahar, M., Lee, S., Guillen, R., & Lee, D. (2025). Generative AI policies under the microscope: how CS conferences are navigating the new frontier in scholarly writing. Communications of the ACM, 68(7), 29-33. [paper link]
[5] Nahar, M., Seo, H., Lee, E. J., Xiong, A., & Lee, D. (2024). Fakes of varying shades: How warning affects human perception and engagement regarding LLM hallucinations. In First Conference on Language Modeling (COLM). [paper link]
[6] Nahar, M., & Ali, M. E. (2022, October). A deep ensemble approach of anger detection from audio-textual conversations. In 2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII) (pp. 1-8). IEEE. [paper link]
[7] Tripto, N. I., Nahar, M., Ali, M. E., Choudhury, F. M., Culpepper, J. S., & Sellis, T. (2019). Top-k trajectories with the best view. GeoInformatica, 23(4), 621-661. [paper link]