| Solar: Deep structured representations for model-based reinforcement learning M Zhang, S Vikram, L Smith, P Abbeel, M Johnson, S Levine International conference on machine learning, 7444-7453, 2019 | 297 | 2019 |
| Pebble: Feedback-efficient interactive reinforcement learning via relabeling experience and unsupervised pre-training K Lee, L Smith, P Abbeel arXiv preprint arXiv:2106.05091, 2021 | 254 | 2021 |
| Avid: Learning multi-stage tasks via pixel-level translation of human videos L Smith, N Dhawan, M Zhang, P Abbeel, S Levine arXiv preprint arXiv:1912.04443, 2019 | 152 | 2019 |
| B-pref: Benchmarking preference-based reinforcement learning K Lee, L Smith, A Dragan, P Abbeel arXiv preprint arXiv:2111.03026, 2021 | 103 | 2021 |
| Efficient online reinforcement learning with offline data PJ Ball, L Smith, I Kostrikov, S Levine International Conference on Machine Learning, 1577-1594, 2023 | 99 | 2023 |
| Legged robots that keep on learning: Fine-tuning locomotion policies in the real world L Smith, JC Kew, XB Peng, S Ha, J Tan, S Levine 2022 International Conference on Robotics and Automation (ICRA), 1593-1599, 2022 | 97 | 2022 |
| A walk in the park: Learning to walk in 20 minutes with model-free reinforcement learning L Smith, I Kostrikov, S Levine arXiv preprint arXiv:2208.07860, 2022 | 88 | 2022 |
| Offline meta-reinforcement learning with online self-supervision VH Pong, AV Nair, LM Smith, C Huang, S Levine International Conference on Machine Learning, 17811-17829, 2022 | 73 | 2022 |
| Learning and adapting agile locomotion skills by transferring experience L Smith, JC Kew, T Li, L Luu, XB Peng, S Ha, J Tan, S Levine arXiv preprint arXiv:2304.09834, 2023 | 47 | 2023 |
| Robopianist: A benchmark for high-dimensional robot control K Zakka, L Smith, N Gileadi, T Howell, XB Peng, S Singh, Y Tassa, ... arXiv preprint arXiv:2304.04150, 2023 | 8 | 2023 |
