Singh, Anikait

16 publications

ICLRW 2025 Improving Test-Time Search for LLMs with Backtracking Against In-Context Value Verifiers Anikait Singh, Kushal Arora, Sedrick Keh, Jean Mercat, Tatsunori Hashimoto, Chelsea Finn, Aviral Kumar

CVPR 2025 Personalized Preference Fine-Tuning of Diffusion Models Meihua Dang, Anikait Singh, Linqi Zhou, Stefano Ermon, Jiaming Song

ICML 2024 Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, Aviral Kumar

NeurIPS 2023 Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Simon Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine

ICLRW 2023 Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine

ICMLW 2023 Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine

CoRL 2023 RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control Brianna Zitkovich, Tianhe Yu, Sichun Xu, Peng Xu, Ted Xiao, Fei Xia, Jialin Wu, Paul Wohlhart, Stefan Welker, Ayzaan Wahid, Quan Vuong, Vincent Vanhoucke, Huong Tran, Radu Soricut, Anikait Singh, Jaspiar Singh, Pierre Sermanet, Pannag R. Sanketi, Grecia Salazar, Michael S. Ryoo, Krista Reymann, Kanishka Rao, Karl Pertsch, Igor Mordatch, Henryk Michalewski, Yao Lu, Sergey Levine, Lisa Lee, Tsang-Wei Edward Lee, Isabel Leal, Yuheng Kuang, Dmitry Kalashnikov, Ryan Julian, Nikhil J. Joshi, Alex Irpan, Brian Ichter, Jasmine Hsu, Alexander Herzog, Karol Hausman, Keerthana Gopalakrishnan, Chuyuan Fu, Pete Florence, Chelsea Finn, Kumar Avinava Dubey, Danny Driess, Tianli Ding, Krzysztof Marcin Choromanski, Xi Chen, Yevgen Chebotar, Justice Carbajal, Noah Brown, Anthony Brohan, Montserrat Gonzalez Arenas, Kehang Han

NeurIPS 2023 ReDS: Offline RL with Heteroskedastic Datasets via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

NeurIPSW 2023 Robotic Offline RL from Internet Videos via Value-Function Pre-Training Chethan Anand Bhateja, Derek Guo, Dibya Ghosh, Anikait Singh, Manan Tomar, Quan Vuong, Yevgen Chebotar, Sergey Levine, Aviral Kumar

NeurIPSW 2022 Offline Reinforcement Learning from Heteroskedastic Data via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

NeurIPSW 2022 Offline Reinforcement Learning from Heteroskedastic Data via Support Constraints Anikait Singh, Aviral Kumar, Quan Vuong, Yevgen Chebotar, Sergey Levine

NeurIPSW 2022 Pre-Training for Robots: Leveraging Diverse Multitask Data via Offline Reinforcement Learning Anikait Singh, Aviral Kumar, Frederik Ebert, Yanlai Yang, Chelsea Finn, Sergey Levine

NeurIPSW 2022 Pre-Training for Robots: Leveraging Diverse Multitask Data via Offline Reinforcement Learning Aviral Kumar, Anikait Singh, Frederik Ebert, Yanlai Yang, Chelsea Finn, Sergey Levine

ICLR 2022 Should I Run Offline Reinforcement Learning or Behavioral Cloning? Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine

CoRL 2021 A Workflow for Offline Model-Free Robotic Reinforcement Learning Aviral Kumar, Anikait Singh, Stephen Tian, Chelsea Finn, Sergey Levine

NeurIPSW 2021 Should I Run Offline Reinforcement Learning or Behavioral Cloning? Aviral Kumar, Joey Hong, Anikait Singh, Sergey Levine