| 2025 | ICML | Potemkin Understanding in Large Language Models. | Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan |
| 2025 | ICML | What Has a Foundation Model Found? Using Inductive Bias to Probe for World Models. | Keyon Vafa, Peter G. Chang, Ashesh Rambachan, Sendhil Mullainathan |
| 2025 | IJCNLP | Critical Thinking: Which Kinds of Complexity Govern Optimal Reasoning Length? | Celine Lee, Alexander M. Rush, Keyon Vafa |
| 2024 | ICML | Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function. | Keyon Vafa, Ashesh Rambachan, Sendhil Mullainathan |
| 2023 | ACL | An Invariant Learning Characterization of Controlled Text Generation. | Carolina Zheng, Claudia Shi, Keyon Vafa, Amir Feder, David M. Blei |
| 2021 | EMNLP | Rationales for Sequential Predictions. | Keyon Vafa, Yuntian Deng, David M. Blei, Alexander M. Rush |
| 2021 | WWW | Assessing the Effects of Friend-to-Friend Texting onTurnout in the 2018 US Midterm Elections. | Aaron Schein, Keyon Vafa, Dhanya Sridhar, Victor Veitch, Jeffrey Quinn, James Moffet, David M. Blei, Donald P. Green |
| 2020 | ACL | Text-Based Ideal Points. | Keyon Vafa, Suresh Naidu, David M. Blei |
| 2019 | ICLR | Discrete Flows: Invertible Generative Models of Discrete Data. | Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole |