| Palm-e: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 954 | 2023 |
| Rt-1: Robotics transformer for real-world control at scale A Brohan, N Brown, J Carbajal, Y Chebotar, J Dabis, C Finn, ... arXiv preprint arXiv:2212.06817, 2022 | 492 | 2022 |
| Rt-2: Vision-language-action models transfer web knowledge to robotic control A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ... arXiv preprint arXiv:2307.15818, 2023 | 354 | 2023 |
| Better exploration with optimistic actor critic K Ciosek, Q Vuong, R Loftin, K Hofmann Advances in Neural Information Processing Systems 32, 2019 | 156 | 2019 |
| First order constrained optimization in policy space Y Zhang, Q Vuong, K Ross Advances in Neural Information Processing Systems, 2020 | 129 | 2020 |
| 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 | 98 | 2023 |
| Open-world object manipulation using pre-trained vision-language models A Stone, T Xiao, Y Lu, K Gopalakrishnan, KH Lee, Q Vuong, P Wohlhart, ... arXiv preprint arXiv:2303.00905, 2023 | 70 | 2023 |
| Rt-2: Vision-language-action models transfer web knowledge to robotic control B Zitkovich, T Yu, S Xu, P Xu, T Xiao, F Xia, J Wu, P Wohlhart, S Welker, ... Conference on Robot Learning, 2165-2183, 2023 | 64 | 2023 |
| Multi-task Batch Reinforcement Learning with Metric Learning J Li, Q Vuong, S Liu, M Liu, K Ciosek, H Iskov Christensen, H Su Neural Information Processing Systems, arXiv: 1909.11373, 2020 | 49 | 2020 |
| How to pick the domain randomization parameters for sim-to-real transfer of reinforcement learning policies? Q Vuong, S Vikram, H Su, S Gao, HI Christensen Learning Legged Locomotion Workshop at IEEE International Conference on …, 2019 | 43 | 2019 |
| Striving for simplicity and performance in off-policy DRL: Output normalization and non-uniform sampling C Wang, Y Wu, Q Vuong, K Ross International Conference on Machine Learning, 10070-10080, 2020 | 39 | 2020 |
| Bridgedata v2: A dataset for robot learning at scale HR Walke, K Black, TZ Zhao, Q Vuong, C Zheng, P Hansen-Estruch, ... Conference on Robot Learning, 1723-1736, 2023 | 37 | 2023 |
| Q-transformer: Scalable offline reinforcement learning via autoregressive q-functions Y Chebotar, Q Vuong, K Hausman, F Xia, Y Lu, A Irpan, A Kumar, T Yu, ... Conference on Robot Learning, 3909-3928, 2023 | 36 | 2023 |
| Octo: An open-source generalist robot policy OM Team, D Ghosh, H Walke, K Pertsch, K Black, O Mees, S Dasari, ... arXiv preprint arXiv:2405.12213, 2024 | 32 | 2024 |
| Supervised Policy Update Q Vuong, Y Zhang, K Ross International Conference on Learning Representations 2019, 2018 | 27* | 2018 |
| Efficient Entropy For Policy Gradient with Multi-Dimensional Action Space (3 page abstract) Y Zhang, QH Vuong, K Song, XY Gong, KW Ross International Conference on Learning Representations 2018 Workshop, 2018 | 13* | 2018 |
| PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs S Nasiriany, F Xia, W Yu, T Xiao, J Liang, I Dasgupta, A Xie, D Driess, ... arXiv preprint arXiv:2402.07872, 2024 | 12 | 2024 |
| Open x-embodiment: Robotic learning datasets and RT-x models Q Vuong, S Levine, HR Walke, K Pertsch, A Singh, R Doshi, C Xu, J Luo, ... Towards Generalist Robots: Learning Paradigms for Scalable Skill Acquisition …, 2023 | 12 | 2023 |
| Offline rl with realistic datasets: Heteroskedasticity and support constraints A Singh, A Kumar, Q Vuong, Y Chebotar, S Levine arXiv preprint arXiv:2211.01052, 2022 | 12 | 2022 |
| Autort: Embodied foundation models for large scale orchestration of robotic agents M Ahn, D Dwibedi, C Finn, MG Arenas, K Gopalakrishnan, K Hausman, ... arXiv preprint arXiv:2401.12963, 2024 | 11 | 2024 |
Sergey LevineUC Berkeley, Physical Intelligence在 eecs.berkeley.edu 的电子邮件经过验证
