| TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP J Morris, E Lifland, JY Yoo, J Grigsby, D Jin, Y Qi Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 1007 | 2020 |
| Long-range transformers for dynamic spatiotemporal forecasting J Grigsby, Z Wang, N Nguyen, Y Qi arXiv preprint arXiv:2109.12218, 2021 | 203 | 2021 |
| Amago: Scalable in-context reinforcement learning for adaptive agents J Grigsby, L Fan, Y Zhu The Twelfth International Conference on Learning Representations, 2023 | 57 | 2023 |
| Measuring Visual Generalization in Continuous Control from Pixels J Grigsby, Y Qi NeurIPS 2020 Workshop on Deep Reinforcement Learning, 2020 | 34 | 2020 |
| Deep learning analysis of deeply virtual exclusive photoproduction J Grigsby, B Kriesten, J Hoskins, S Liuti, P Alonzi, M Burkardt Physical Review D 104 (1), 016001, 2021 | 31 | 2021 |
| PGrad: Learning Principal Gradients For Domain Generalization Z Wang, J Grigsby, Y Qi arXiv preprint arXiv:2305.01134, 2023 | 24 | 2023 |
| RARE: Renewable Energy Aware Resource Management in Datacenters V Venkataswamy, J Grigsby, A Grimshaw, Y Qi Workshop on Job Scheduling Strategies for Parallel Processing, 108-130, 2022 | 20 | 2022 |
| AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers J Grigsby, J Sasek, S Parajuli, D Adebi, A Zhang, Y Zhu The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024 | 13 | 2024 |
| Cross-episodic curriculum for transformer agents LX Shi, Y Jiang, J Grigsby, L Fan, Y Zhu Advances in Neural Information Processing Systems 36, 13-34, 2023 | 10 | 2023 |
| Towards Automatic Actor-Critic Solutions to Continuous Control J Grigsby, JY Yoo, Y Qi NeurIPS 2021 Workshop on Deep Reinforcement Learning, 2021 | 10 | 2021 |
| ST-MAML: A stochastic-task based method for task-heterogeneous meta-learning Z Wang, J Grigsby, A Sekhon, Y Qi Uncertainty in Artificial Intelligence, 2066-2074, 2022 | 9 | 2022 |
| A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets J Grigsby, Y Qi arXiv preprint arXiv:2110.04698, 2021 | 5 | 2021 |
| VLM Q-Learning: Aligning Vision-Language Models for Interactive Decision-Making J Grigsby, Y Zhu, MS Ryoo, JC Niebles Scaling Self-Improving Foundation Models without Human Supervision, 2025 | 2 | 2025 |
| Human-Level Competitive Pok\'emon via Scalable Offline Reinforcement Learning with Transformers J Grigsby, Y Xie, J Sasek, S Zheng, Y Zhu arXiv preprint arXiv:2504.04395, 2025 | | 2025 |
