IR-1386: (2026) Chang, H., Gomez, J., Patwari, M., Sajith, A. and Zamani, H., "Your Mouse and Eyes Secretly Leak Your Preference: LLM Alignment using Implicit Feedback from Users," In The Second Workshop for Research on Agent Language Models (REALM 2026) at the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), Budapest, Hungary, October 24-29, 2026. [View Abstract] [View bibtex]
IR-1365: (2026) Bhuiya, N., Dasgupta, S., McCallum, A. and Chang, H., "Prompt2Box: Uncovering Entailment Structure among LLM Prompts," To appear in the Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP 2026), Budapest, Hungary, Oct. 24-29, 2026. [View Abstract] [View bibtex]
IR-1347: (2025) Joshi, B., Venkatapathy, S., Bansal, M., Peng, N. and Chang, H., "🥤CoKe: Customizable Fine-Grained Story Evaluation via Chain-of-Keyword Rationalization," in Proceedings of the Fourth Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2025), as part of ACL 2025, Vienna, Austria. July 27-Aug. 1, 2025 [View Abstract] [View bibtex]
IR-1343: (2025) Hou, Z., Zhang, B., Lu, Y., Baghel, B., Brei, A., Lu, X., Jiang, M., Brahman, F., Chaturvedi, S., Chang, H., Khashabi, D. and Li, X., "CreativityPrism: A Holistic Benchmark for Machine Creativity 💡💎🌈," In Transactions on Machine Learning Research (TMLR), July 2026. [View Abstract] [View bibtex]
IR-1342: (2025) Chang, H., Peng, N., Bansal, M., Ramakrishna, A. and Chung, T., "REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation by Extrapolating the Entropy of an Infinitely Large LM," In Transactions of the Association for Computational Linguistics, July 18, 2025, Vol. 13, pp. 760-783. [View Abstract] [View bibtex]
IR-1335: (2024) Atmakuru, A., Nainani, J., Bheemreddy, R., Lakkaraju, A., Yao, Z., Zamani, H. and Chang, H., "CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraints," Presented at the 6th Workshop on Narrative Understanding (WNU), at the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, FL, USA, Nov. 15, 2024 [View Abstract] [View bibtex]
IR-1334: (2024) Chang, H., Peng, N., Bansal, M., Ramakrishna, A. and Chung, T., "Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM," in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, FL, USA, Nov. 12-16, 2024, pp. 8503-8526. [View Abstract] [View bibtex]