| 2025 | ACL | LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. | Thai Quoc Hoang, Kung-Hsiang Huang, Shirley Kokane, Jianguo Zhang, Zuxin Liu, Ming Zhu, Jake Grigsby, Tian Lan, Michael S. Ryoo, Chien-Sheng Wu, Shelby Heinecke, Huan Wang, Silvio Savarese, Caiming Xiong, Juan Carlos Niebles |
| 2024 | ICLR | AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents. | Jake Grigsby, Linxi Fan, Yuke Zhu |
| 2024 | JSSPP | Launchpad: Learning to Schedule Using Offline and Online RL Methods. | Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi |
| 2023 | ICLR | PGrad: Learning Principal Gradients For Domain Generalization. | Zhe Wang, Jake Grigsby, Yanjun Qi |
| 2022 | JSSPP | RARE: Renewable Energy Aware Resource Management in Datacenters. | Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi |
| 2022 | UAI | ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. | Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi |
| 2020 | EMNLP | TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP. | John X. Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, Yanjun Qi |