Large Language Model
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Beyond the Response: Examining Reasoning and Execution Fidelity in Large Language Models for Mental Health
Qadir, Sarvech; Ni, Congning; Vaidya, Mihir Sachin; Ryu, Hyeyoung; Mulvaney, Shelagh A.; Kantarcioglu, Murat; Novak, Laurie Lovett; Malin, Bradley; Rose, Susannah Leigh; Yin, Zhijun. (2026). Beyond the response: Examining reasoning and execution fidelity in large language models for mental health. Proceedings of the 9th ACM Conference on Fairness, Accountability,… Read MoreJul. 28, 2026
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A Survey on LLM-based Conversational User Simulation
Ni, Bo; Wang, Leyao; Wang, Yu; Kveton, Branislav; Dernoncourt, Franck; Xia, Yu; Chen, Hongjie; Leura, Reuben; Basu, Samyadeep; Mukherjee, Subhojyoti; Mathur, Puneet; Ahmed, Nesreen; Wu, Junda; Li, Li; Zhang, Huixin; Zhang, Ruiyi; Yu, Tong; Kim, Sungchul; Gu, Jiuxiang; Tu, Zhengzhong; Siu, Alexa; Wang, Zichao; Yoon, David Seunghyun; Lipka,… Read MoreJun. 17, 2026
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Ensemble Privacy Defense for Knowledge-Intensive LLMs against Membership Inference Attacks
Fu, Haowei; Ni, Bo; Xu, Han; Liu, Kunpeng; Lin, Dan; Derr, Tyler. (2026). Ensemble privacy defense for knowledge-intensive LLMs against membership inference attacks. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics: Findings of EACL 2026, 2786–2799. https://doi.org/10.18653/v1/2026.findings-eacl.145 Retrieval-Augmented Generation, or… Read MoreJun. 17, 2026
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A Novel Approach to Evaluating the Effectiveness of Large Language Models for Multimodal Analysis of Embodied Learning in Classrooms
Fonteles, Joyce Horn; Sivakumaran, Nithin; Cohn, Clayton; Coursey, Austin; Yu, Shoubin; Stengel-Eskin, Elias; Ashwin, T. S.; Bansal, Mohit; Biswas, Gautam. (2026). A novel approach to evaluating the effectiveness of large language models for multimodal analysis of embodied learning in classrooms. 16th International Learning Analytics and Knowledge Conference, LAK 2026,… Read MoreJun. 17, 2026
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Using Large Language Models to Detect Socially Shared Regulation of Collaborative Learning
Zhang, Jiayi; Borchers, Conrad; Cohn, Clayton; Srivastava, Namarata; Snyder, Caitlin; Guo, Siyuan; Ashwin, T. S.; Mohammed, Naveeduddin; Noh, Haley; Biswas, Gautam. (2026). Using large language models to detect socially shared regulation of collaborative learning. 16th International Learning Analytics and Knowledge Conference, LAK 2026, 883–890. https://doi.org/10.1145/3785022.3785083 The field… Read MoreJun. 17, 2026
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The Role of LLM-Powered Conversational Agents in Supporting Inquiry in a Narrative-Centered Learning Environment: A Learning Analytics Study
Srivastava, Namrata; Humburg, Megan; Burriss, Sarah; Jain, Shruti; Cohn, Clayton; Kim, Yeojin; Timalsina, Umesh; Danish, Joshua; Hmelo-Silver, Cindy E.; Glazewski, Krista; Lester, James; Biswas, Gautam. (2026). The role of LLM-powered conversational agents in supporting inquiry in a narrative-centered learning environment: A learning analytics study. In 16th International Learning Analytics… Read MoreJun. 17, 2026
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ComCat: Expertise-Guided Context Generation to Enhance Code Comprehension
Skyler Grandel; Scott Thomas Andersen; Yu Huang; Kevin Leach (2026). ComCat: Expertise-guided context generation to enhance code comprehension. ACM Transactions on Software Engineering and Methodology, 35(3), Article 82. https://doi.org/10.1145/3742475 Software maintenance makes up a large share of the total cost of software over its lifetime, and a big… Read MoreMar. 26, 2026
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Demystifying the Power of Large Language Models in Graph Structure Generation
Wang, Yu; Rossi, Ryan A.; Park, Namyong; Ahmed, Nesreen K.; Koutra, Danai; Dernoncourt, Franck; & Derr, Tyler. (2025). Demystifying the power of large language models in graph structure generation. 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Proceedings of the Conference… Read MoreFeb. 25, 2026
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Knowledge distillation and dataset distillation of large language models: emerging trends, challenges, and future directions
Fang, L., Yu, X., Cai, J., Chen, Y., Wu, S., Liu, Z., Yang, Z., Lu, H., Gong, X., Liu, Y., Ma, T., Ruan, W., Abbasi, A., Zhang, J., Wang, T., Latif, E., Liu, W., Zhang, W., Kolouri, S., Zhai, X., Zhu, D., Zhong, W., Liu, T., & Ma,… Read MoreDec. 19, 2025
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Enhancing Code LLM Training with Programmer Attention
Zhang, Yifan, Huang, Chen, Karas, Zachary, Nguyen, Thuy Dung, Leach, Kevin, & Huang, Yu. (2025). Enhancing Code LLM Training with Programmer Attention. Proceedings of the ACM SIGSOFT Symposium on the Foundations of Software Engineering. https://doi.org/10.1145/3696630.3728510 Human attention, such as where programmers look while reading… Read MoreSep. 26, 2025