Scaling Simulation-to-Real Transfer by Learning Composable Robot Skills. - Ryan Julian; Eric Heiden; Zhanpeng He; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (ISER, 2018)

Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation. - Hejia Zhang; Eric Heiden; Ryan Julian; Zhangpeng He; Joseph J. Lim; Gaurav S. Sukhatme (CoRR, 2018)

Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations. - Zhanpeng He; Ryan Julian; Eric Heiden; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (CoRR, 2018)

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 (CoRL, 2019)

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning. - Ryan Julian; Benjamin Swanson; Gaurav S. Sukhatme; Sergey Levine; Chelsea Finn; Karol Hausman (CoRL, 2020)

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation. - Ryan Julian; Benjamin Swanson; Gaurav S. Sukhatme; Sergey Levine; Chelsea Finn; Karol Hausman (CoRR, 2020)

Scaling simulation-to-real transfer by learning a latent space of robot skills. - Ryan Julian; Eric Heiden; Zhanpeng He; Hejia Zhang; Stefan Schaal; Joseph J. Lim; Gaurav S. Sukhatme; Karol Hausman (Int. J. Robotics Res., 2020)

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. - Yevgen Chebotar; Karol Hausman; Yao Lu 006; Ted Xiao; Dmitry Kalashnikov; Jacob Varley; Alex Irpan; Benjamin Eysenbach; Ryan Julian; Chelsea Finn; Sergey Levine (ICML, 2021)

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. - Yevgen Chebotar; Karol Hausman; Yao Lu 006; Ted Xiao; Dmitry Kalashnikov; Jake Varley; Alex Irpan; Benjamin Eysenbach; Ryan Julian; Chelsea Finn; Sergey Levine (CoRR, 2021)

Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning. - K. R. Zentner; Ryan Julian; Ujjwal Puri; Yulun Zhang 002; Gaurav S. Sukhatme (CoRR, 2021)

A Simple Approach to Continual Learning by Transferring Skill Parameters. - K. R. Zentner; Ryan Julian; Ujjwal Puri; Yulun Zhang 002; Gaurav S. Sukhatme (CoRR, 2021)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Brian Ichter; Anthony Brohan; Yevgen Chebotar; Chelsea Finn; Karol Hausman; Alexander Herzog; Daniel Ho; Julian Ibarz; Alex Irpan; Eric Jang; Ryan Julian; Dmitry Kalashnikov; et al. (CoRL, 2022)

Efficient Multi-Task Learning via Iterated Single-Task Transfer. - K. R. Zentner; Ujjwal Puri; Yulun Zhang 002; Ryan Julian; Gaurav S. Sukhatme (IROS, 2022)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Michael Ahn; Anthony Brohan; Noah Brown; Yevgen Chebotar; Omar Cortes; Byron David; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Daniel Ho; Jasmine Hsu; et al. (CoRR, 2022)

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. - Brianna Zitkovich; Tianhe Yu; Sichun Xu; Peng Xu 010; Ted Xiao; Fei Xia 002; Jialin Wu; Paul Wohlhart; Stefan Welker; Ayzaan Wahid; Quan Vuong; Vincent Vanhoucke; et al. (CoRL, 2023)

RT-1: Robotics Transformer for Real-World Control at Scale. - Anthony Brohan; Noah Brown; Justice Carbajal; Yevgen Chebotar; Joseph Dabis; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Jasmine Hsu; Julian Ibarz; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (CoRR, 2023)

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. - Abby O'Neill; Abdul Rehman; Abhiram Maddukuri; Abhishek Gupta 004; Abhishek Padalkar; Abraham Lee; Acorn Pooley; Agrim Gupta; Ajay Mandlekar; Ajinkya Jain; Albert Tung; Alex Bewley; et al. (ICRA, 2024)

Conditionally Combining Robot Skills using Large Language Models. - K. R. Zentner; Ryan Julian; Brian Ichter; Gaurav S. Sukhatme (ICRA, 2024)

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. - Michael Ahn; Debidatta Dwibedi; Chelsea Finn; Montse Gonzalez Arenas; Keerthana Gopalakrishnan; Karol Hausman; Brian Ichter; Alex Irpan; Nikhil J. Joshi; Ryan Julian; Sean Kirmani; Isabel Leal; et al. (CoRR, 2024)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 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; Jordan K. Terry; Isaac Woungang; Nariman Farsad; Pablo Samuel Castro (CoRR, 2025)