| 2026 | ACL | MalruleLib: Large-Scale Executable Misconception Reasoning with Step Traces for Modeling Student Thinking in Mathematics. | Xinghe Chen, Naiming Liu, Shashank Sonkar |
| 2026 | AIED | Circuit Complexity of Hierarchical Knowledge Tracing. | Naiming Liu, Richard G. Baraniuk, Shashank Sonkar |
| 2026 | AIED | Misconception Acquisition Dynamics in Large Language Models. | Naiming Liu, Xinghe Chen, Richard G. Baraniuk, Mrinmaya Sachan, Shashank Sonkar |
| 2026 | EACL | CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models. | Naiming Liu, Richard G. Baraniuk, Shashank Sonkar |
| 2025 | AIED | Do LLMs Make Mistakes Like Students? Exploring Natural Alignments Between Language Models and Human Error Patterns. | Naiming Liu, Shashank Sonkar, Richard G. Baraniuk |
| 2025 | AIED | Training LLM-Based Tutors to Improve Student Learning Outcomes in Dialogues. | Alexander Scarlatos, Naiming Liu, Jaewook Lee, Richard G. Baraniuk, Andrew S. Lan |
| 2025 | AIED | Many-Shot Regurgitation Prompting. | Shashank Sonkar, Naiming Liu, Richard G. Baraniuk |
| 2025 | AIED | Turing-Like Test for Personalized Educational AI. | Shashank Sonkar, Naiming Liu, Xinghe Chen, Richard G. Baraniuk |
| 2025 | LAK | Atomic Learning Objectives and LLMs Labeling: A High-Resolution Approach for Physics Education. | Naiming Liu, Shashank Sonkar, Debshila Basu Mallick, Richard G. Baraniuk, Zhongzhou Chen |
| 2024 | AIED | Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits. | Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2024 | EMNLP | Student Data Paradox and Curious Case of Single Student-Tutor Model: Regressive Side Effects of Training LLMs for Personalized Learning. | Shashank Sonkar, Naiming Liu, Richard G. Baraniuk |
| 2024 | EMNLP | MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education. | Shashank Sonkar, Naiming Liu, Myco Le, Richard G. Baraniuk |
| 2024 | ICASSP | Titan: Bringing the Deep Image Prior to Implicit Representations. | Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk |
| 2024 | LAK | Code Soliloquies for Accurate Calculations in Large Language Models. | Shashank Sonkar, Xinghe Chen, Myco Le, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2023 | EMNLP | CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principles. | Shashank Sonkar, Naiming Liu, Debshila Basu Mallick, Richard G. Baraniuk |
| 2022 | AIED | Automated Scoring for Reading Comprehension via In-context BERT Tuning. | Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benot Choffin, Richard G. Baraniuk, Andrew S. Lan |
| 2022 | EMNLP | Open-ended Knowledge Tracing for Computer Science Education. | Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan |
| 2022 | ICASSP | NFT-K: Non-Fungible Tangent Kernels. | Sina Alemohammad, Hossein Babaei, C. J. Barberan, Naiming Liu, Lorenzo Luzi, Blake Mason, Richard G. Baraniuk |
| 2021 | ICASSP | Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. | Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk |