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 (EMNLP (Demos), 2020)

Measuring Visual Generalization in Continuous Control from Pixels. - Jake Grigsby; Yanjun Qi (CoRR, 2020)

Towards Automatic Actor-Critic Solutions to Continuous Control. - Jake Grigsby; Jin Yong Yoo; Yanjun Qi (CoRR, 2021)

Long-Range Transformers for Dynamic Spatiotemporal Forecasting. - Jake Grigsby; Zhe Wang 025; Yanjun Qi (CoRR, 2021)

A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets. - Jake Grigsby; Yanjun Qi (CoRR, 2021)

RARE: Renewable Energy Aware Resource Management in Datacenters. - Vanamala Venkataswamy; Jake Grigsby; Andrew Grimshaw; Yanjun Qi (JSSPP, 2022)

ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. - Zhe Wang 025; Jake Grigsby; Arshdeep Sekhon; Yanjun Qi (UAI, 2022)

PGrad: Learning Principal Gradients For Domain Generalization. - Zhe Wang 025; Jake Grigsby; Yanjun Qi (ICLR, 2023)

Cross-Episodic Curriculum for Transformer Agents. - Lucy Xiaoyang Shi; Yunfan Jiang 001; Jake Grigsby; Linxi Fan; Yuke Zhu (NeurIPS, 2023)

AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents. - Jake Grigsby; Linxi Fan; Yuke Zhu (ICLR, 2024)

Launchpad: Learning to Schedule Using Offline and Online RL Methods. - Vanamala Venkataswamy; Jake Grigsby; Andrew Grimshaw; Yanjun Qi (JSSPP, 2024)

AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers. - Jake Grigsby; Justin Sasek; Samyak Parajuli; Daniel Adebi; Amy Zhang 001; Yuke Zhu (NeurIPS, 2024)

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 014; et al. (ACL (Findings), 2025)

Human-Level Competitive Pokémon via Scalable Offline Reinforcement Learning with Transformers. - Jake Grigsby; Yuqi Xie; Justin Sasek; Steven Zheng; Yuke Zhu (CoRR, 2025)

VLM Q-Learning: Aligning Vision-Language Models for Interactive Decision-Making. - Jake Grigsby; Yuke Zhu; Michael S. Ryoo; Juan Carlos Niebles (CoRR, 2025)

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. - Thai Hoang; Kung-Hsiang Huang; Shirley Kokane; Jianguo Zhang 005; Zuxin Liu; Ming Zhu; Jake Grigsby; Tian Lan 006; Michael S. Ryoo; Chien-Sheng Wu; Shelby Heinecke; Huan Wang 014; et al. (CoRR, 2025)