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Anikait Singh
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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
453*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
152*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
852021
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
592024
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
452022
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
17*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
162024
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
102023
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
102019
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, ...
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Articles 1–12