| Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning Z Yuan, G Ma, Y Mu, B Xia, B Yuan, X Wang, P Luo, H Xu The 31st International Joint Conference on Artificial Intelligence (IJCAI 2022), 2022 | 19 | 2022 |
| A Comprehensive Survey of Data Augmentation in Visual Reinforcement Learning G Ma, Z Wang, Z Yuan, X Wang, B Yuan, D Tao arXiv preprint arXiv:2210.04561, 2022 | 18 | 2022 |
| Are Large Language Models Really Robust to Word-Level Perturbations? H Wang, G Ma, C Yu, N Gui, L Zhang, Z Huang, S Ma, Y Chang, S Zhang, ... Socially Responsible Language Modelling Research (SoLaR) Workshop at NeurIPS'23, 2023 | 9 | 2023 |
| Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping H Wang, G Ma, Z Meng, Z Qin, L Shen, Z Zhang, B Wu, L Liu, Y Bian, T Xu, ... arXiv preprint arXiv:2402.07610, 2024 | 3 | 2024 |
| Normalization Enhances Generalization in Visual Reinforcement Learning L Li, J Lyu, G Ma, Z Wang, Z Yang, X Li, Z Li AAMAS 2024 (Oral); Generalization in Planning Workshop @ NeurIPS 2023, 2023 | 3 | 2023 |
| Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning G Ma, L Zhang, H Wang, L Li, Z Wang, Z Wang, L Shen, X Wang, D Tao 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023 | 2 | 2023 |
| Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages G Ma*, L Li*, S Zhang, Z Liu, Z Wang, Y Chen, L Shen, X Wang, D Tao The Twelfth International Conference on Learning Representations (ICLR 2024), 2024 | 1 | 2024 |
