| Towards more generalizable one-shot visual imitation learning Z Mandi, F Liu, K Lee, P Abbeel 2022 International Conference on Robotics and Automation (ICRA), 2434-2444, 2022 | 45 | 2022 |
| Roco: Dialectic multi-robot collaboration with large language models Z Mandi, S Jain, S Song arXiv preprint arXiv:2307.04738, 2023 | 44 | 2023 |
| Cacti: A framework for scalable multi-task multi-scene visual imitation learning Z Mandi, H Bharadhwaj, V Moens, S Song, A Rajeswaran, V Kumar arXiv preprint arXiv:2212.05711, 2022 | 30 | 2022 |
| On the effectiveness of fine-tuning versus meta-reinforcement learning Z Mandi, P Abbeel, S James arXiv preprint arXiv:2206.03271, 2022 | 27 | 2022 |
| ZPD teaching strategies for deep reinforcement learning from demonstrations D Seita, D Chan, R Rao, C Tang, M Zhao, J Canny arXiv preprint arXiv:1910.12154, 2019 | 11 | 2019 |
| On the effectiveness of fine-tuning versus meta-reinforcement learning M Zhao, P Abbeel, S James Advances in Neural Information Processing Systems 35, 26519-26531, 2022 | 8 | 2022 |
| Md-splatting: Learning metric deformation from 4d gaussians in highly deformable scenes BP Duisterhof, Z Mandi, Y Yao, JW Liu, MZ Shou, S Song, J Ichnowski arXiv preprint arXiv:2312.00583, 2023 | 6 | 2023 |
| On the effectiveness of fine-tuning versus meta-RL for robot manipulation Z Mandi, P Abbeel, S James CoRL 2022 Workshop on Pre-training Robot Learning, 2022 | 3 | 2022 |
| DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning D Seita, A Gopal, Z Mandi, J Canny arXiv preprint arXiv:2109.07380, 2021 | | 2021 |
