Yu, Tianhe

34 publications

NeurIPS 2025 Meta-World+: An Improved, Standardized, RL Benchmark Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Tianhe Yu, Zhanpeng He, K.R. Zentner, Ryan Julian, J K Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro
ICLR 2025 RRM: Robust Reward Model Training Mitigates Reward Hacking Tianqi Liu, Wei Xiong, Jie Ren, Lichang Chen, Junru Wu, Rishabh Joshi, Yang Gao, Jiaming Shen, Zhen Qin, Tianhe Yu, Daniel Sohn, Anastasia Makarova, Jeremiah Zhe Liu, Yuan Liu, Bilal Piot, Abe Ittycheriah, Aviral Kumar, Mohammad Saleh
CoRL 2024 RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches Priya Sundaresan, Quan Vuong, Jiayuan Gu, Peng Xu, Ted Xiao, Sean Kirmani, Tianhe Yu, Michael Stark, Ajinkya Jain, Karol Hausman, Dorsa Sadigh, Jeannette Bohg, Stefan Schaal
ICLR 2024 Video Language Planning Yilun Du, Sherry Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Andy Zeng, Jonathan Tompson
CoRL 2024 What Makes Pre-Trained Visual Representations Successful for Robust Manipulation? Kaylee Burns, Zach Witzel, Jubayer Ibn Hamid, Tianhe Yu, Chelsea Finn, Karol Hausman
L4DC 2023 Contrastive Example-Based Control Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
AAAI 2023 Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching Lantao Yu, Tianhe Yu, Jiaming Song, Willie Neiswanger, Stefano Ermon
ICML 2023 PaLM-E: An Embodied Multimodal Language Model Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence
CoRL 2023 Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions Yevgen Chebotar, Quan Vuong, Karol Hausman, Fei Xia, Yao Lu, Alex Irpan, Aviral Kumar, Tianhe Yu, Alexander Herzog, Karl Pertsch, Keerthana Gopalakrishnan, Julian Ibarz, Ofir Nachum, Sumedh Anand Sontakke, Grecia Salazar, Huong T. Tran, Jodilyn Peralta, Clayton Tan, Deeksha Manjunath, Jaspiar Singh, Brianna Zitkovich, Tomas Jackson, Kanishka Rao, Chelsea Finn, 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
NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
ICML 2022 How to Leverage Unlabeled Data in Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Chelsea Finn, Sergey Levine
NeurIPS 2022 LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning Xi Chen, Ali Ghadirzadeh, Tianhe Yu, Jianhao Wang, Alex Yuan Gao, Wenzhe Li, Liang Bin, Chelsea Finn, Chongjie Zhang
CoRL 2022 Offline Reinforcement Learning at Multiple Frequencies Kaylee Burns, Tianhe Yu, Chelsea Finn, Karol Hausman
NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
NeurIPS 2021 COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
NeurIPS 2021 Conservative Data Sharing for Multi-Task Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Karol Hausman, Sergey Levine, Chelsea Finn
NeurIPSW 2021 Data Sharing Without Rewards in Multi-Task Offline Reinforcement Learning Tianhe Yu, Aviral Kumar, Yevgen Chebotar, Chelsea Finn, Sergey Levine, Karol Hausman
NeurIPS 2021 Efficiently Identifying Task Groupings for Multi-Task Learning Chris Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
L4DC 2021 Offline Reinforcement Learning from Images with Latent Space Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
NeurIPSW 2021 The Reflective Explorer: Online Meta-Exploration from Offline Data in Realistic Robotic Tasks Rafael Rafailov, Varun Kumar Vijay, Tianhe Yu, Avi Singh, Mariano Phielipp, Chelsea Finn
NeurIPS 2021 Visual Adversarial Imitation Learning Using Variational Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
ICMLW 2021 Visual Adversarial Imitation Learning Using Variational Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
NeurIPS 2020 Gradient Surgery for Multi-Task Learning Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
NeurIPS 2020 MOPO: Model-Based Offline Policy Optimization Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y Zou, Sergey Levine, Chelsea Finn, Tengyu Ma
ICML 2020 On the Expressivity of Neural Networks for Deep Reinforcement Learning Kefan Dong, Yuping Luo, Tianhe Yu, Chelsea Finn, Tengyu Ma
NeurIPS 2019 Meta-Inverse Reinforcement Learning with Probabilistic Context Variables Lantao Yu, Tianhe Yu, Chelsea Finn, Stefano Ermon
CoRL 2019 Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, Sergey Levine
ICLR 2017 Generalizing Skills with Semi-Supervised Reinforcement Learning Chelsea Finn, Tianhe Yu, Justin Fu, Pieter Abbeel, Sergey Levine
CoRL 2017 One-Shot Visual Imitation Learning via Meta-Learning Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, Sergey Levine