| 2026 | EACL | ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. | Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier |
| 2025 | AAAI | ModelDiff: Symbolic Dynamic Programming for Model-Aware Policy Transfer in Deep Q-Learning. | Xiaotian Liu, Jihwan Jeong, Ayal Taitler, Michael Gimelfarb, Scott Sanner |
| 2025 | ICML | Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens. | Jihwan Jeong, Xiaoyu Wang, Jingmin Wang, Scott Sanner, Pascal Poupart |
| 2024 | ICLR | Demystifying Embedding Spaces using Large Language Models. | Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier |
| 2023 | CPAIOR | A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic Variable Elimination. | Jihwan Jeong, Scott Sanner, Akshat Kumar |
| 2023 | ICLR | Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization. | Jihwan Jeong, Xiaoyu Wang, Michael Gimelfarb, Hyunwoo Kim, Baher Abdulhai, Scott Sanner |
| 2022 | AAAI | A Distributional Framework for Risk-Sensitive End-to-End Planning in Continuous MDPs. | Noah Patton, Jihwan Jeong, Mike Gimelfarb, Scott Sanner |
| 2022 | ICML | An Exact Symbolic Reduction of Linear Smart Predict+Optimize to Mixed Integer Linear Programming. | Jihwan Jeong, Parth Jaggi, Andrew Butler, Scott Sanner |
| 2021 | AAAI | Online Class-Incremental Continual Learning with Adversarial Shapley Value. | Dongsub Shim, Zheda Mai, Jihwan Jeong, Scott Sanner, Hyunwoo Kim, Jongseong Jang |
| 2021 | IJCAI | Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions. | Jihwan Jeong, Parth Jaggi, Scott Sanner |