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 | 478* | 2023 |
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 | 168* | 2023 |
When should we prefer offline reinforcement learning over behavioral cloning? A Kumar, J Hong, A Singh, S Levine International Conference on Learning Representations, 2021 | 120* | 2021 |
A workflow for offline model-free robotic reinforcement learning A Kumar, A Singh, S Tian, C Finn, S Levine arXiv preprint arXiv:2109.10813, 2021 | 85 | 2021 |
Cal-ql: Calibrated offline rl pre-training for efficient online fine-tuning M Nakamoto, S Zhai, A Singh, M Sobol Mark, Y Ma, C Finn, A Kumar, ... Advances in Neural Information Processing Systems 36, 2024 | 61 | 2024 |
Pre-training for robots: Offline rl enables learning new tasks from a handful of trials A Kumar, A Singh, F Ebert, M Nakamoto, Y Yang, C Finn, S Levine arXiv preprint arXiv:2210.05178, 2022 | 47 | 2022 |
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 |
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 | 18* | 2022 |
Robotic offline rl from internet videos via value-function pre-training C Bhateja, D Guo, D Ghosh, A Singh, M Tomar, Q Vuong, Y Chebotar, ... arXiv preprint arXiv:2309.13041, 2023 | 10 | 2023 |
A mobile application for keyword search in real-world scenes S Pundlik, A Singh, G Baghel, V Baliutaviciute, G Luo IEEE Journal of Translational Engineering in Health and Medicine 7, 1-10, 2019 | 10 | 2019 |
Robotic Offline RL from Internet Videos via Value-Function Learning C Bhateja, D Guo, D Ghosh, A Singh, M Tomar, Q Vuong, Y Chebotar, ... | | |
D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning R Rafailov, KB Hatch, A Singh, A Kumar, L Smith, I Kostrikov, ... | | |