| Direct preference optimization: Your language model is secretly a reward model R Rafailov, A Sharma, E Mitchell, CD Manning, S Ermon, C Finn Advances in Neural Information Processing Systems 36, 2024 | 929 | 2024 |
| Dynamics-aware unsupervised discovery of skills A Sharma, S Gu, S Levine, V Kumar, K Hausman International Conference on Learning Representations (ICLR), 2020, 2019 | 421 | 2019 |
| Open X-Embodiment: Robotic learning Datasets and RT-X Models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... arXiv preprint arXiv:2310.08864, 2023 | 136 | 2023 |
| Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback K Tian, E Mitchell, A Zhou, A Sharma, R Rafailov, H Yao, C Finn, ... arXiv preprint arXiv:2305.14975, 2023 | 104 | 2023 |
| Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning A Sharma, M Ahn, S Levine, V Kumar, K Hausman, S Gu Robotics: Science and Systems (RSS), 2020 | 45 | 2020 |
| Variational empowerment as representation learning for goal-based reinforcement learning J Choi, A Sharma, H Lee, S Levine, SS Gu arXiv preprint arXiv:2106.01404, 2021 | 44* | 2021 |
| Autonomous Reinforcement Learning via Subgoal Curricula A Sharma, A Gupta, S Levine, K Hausman, C Finn Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 36 | 2021 |
| Autonomous Reinforcement Learning: Formalism and Benchmarking A Sharma, K Xu, N Sardana, A Gupta, K Hausman, S Levine, C Finn arXiv preprint arXiv:2112.09605, 2021 | 29* | 2021 |
| Waypoint-Based Imitation Learning for Robotic Manipulation LX Shi, A Sharma, TZ Zhao, C Finn arXiv preprint arXiv:2307.14326, 2023 | 25 | 2023 |
| Preference fine-tuning of llms should leverage suboptimal, on-policy data F Tajwar, A Singh, A Sharma, R Rafailov, J Schneider, T Xie, S Ermon, ... arXiv preprint arXiv:2404.14367, 2024 | 19* | 2024 |
| You Only Live Once: Single-Life Reinforcement Learning A Chen, A Sharma, S Levine, C Finn Advances in Neural Information Processing Systems 35, 14784-14797, 2022 | 18 | 2022 |
| A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning A Sharma, R Ahmad, C Finn arXiv preprint arXiv:2205.05212, 2022 | 18 | 2022 |
| An Emulator for Fine-Tuning Large Language Models using Small Language Models E Mitchell, R Rafailov, A Sharma, C Finn, CD Manning arXiv preprint arXiv:2310.12962, 2023 | 15 | 2023 |
| DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset A Khazatsky, K Pertsch, S Nair, A Balakrishna, S Dasari, S Karamcheti, ... arXiv preprint arXiv:2403.12945, 2024 | 9 | 2024 |
| When to ask for help: Proactive interventions in autonomous reinforcement learning A Xie, F Tajwar, A Sharma, C Finn Advances in Neural Information Processing Systems 35, 16918-16930, 2022 | 9 | 2022 |
| Yell At Your Robot: Improving On-the-Fly from Language Corrections LX Shi, Z Hu, TZ Zhao, A Sharma, K Pertsch, J Luo, S Levine, C Finn arXiv preprint arXiv:2403.12910, 2024 | 7 | 2024 |
| Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning A Sharma, AM Ahmed, R Ahmad, C Finn arXiv preprint arXiv:2303.01488, 2023 | 7 | 2023 |
| Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning J Yang, MS Mark, B Vu, A Sharma, J Bohg, C Finn arXiv preprint arXiv:2310.15145, 2023 | 5 | 2023 |
| A flexible probabilistic framework for large-margin mixture of experts A Sharma, S Saxena, P Rai Machine Learning 108 (8-9), 1369-1393, 2019 | 5 | 2019 |
| A Critical Evaluation of AI Feedback for Aligning Large Language Models A Sharma, S Keh, E Mitchell, C Finn, K Arora, T Kollar arXiv preprint arXiv:2402.12366, 2024 | 4 | 2024 |
Chelsea FinnStanford University, Google在 cs.stanford.edu 的电子邮件经过验证
