Goal-driven dynamics learning via Bayesian optimization. - Somil Bansal; Roberto Calandra; Ted Xiao; Sergey Levine; Claire J. Tomlin (CDC, 2017)

Learning Latent Plans from Play. - Corey Lynch; Mohi Khansari; Ted Xiao; Vikash Kumar; Jonathan Tompson; Sergey Levine; Pierre Sermanet (CoRL, 2019)

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. - Ted Xiao; Eric Jang; Dmitry Kalashnikov; Sergey Levine; Julian Ibarz; Karol Hausman; Alexander Herzog (ICLR, 2020)

AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRL, 2021)

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)

AW-Opt: Learning Robotic Skills with Imitation and Reinforcement at Scale. - Yao Lu 006; Karol Hausman; Yevgen Chebotar; Mengyuan Yan; Eric Jang; Alexander Herzog; Ted Xiao; Alex Irpan; Mohi Khansari; Dmitry Kalashnikov; Sergey Levine (CoRR, 2021)

Inner Monologue: Embodied Reasoning through Planning with Language Models. - Wenlong Huang; Fei Xia 002; Ted Xiao; Harris Chan; Jacky Liang; Pete Florence; Andy Zeng 001; Jonathan Tompson; Igor Mordatch; Yevgen Chebotar; Pierre Sermanet; Tomas Jackson; et al. (CoRL, 2022)

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)

PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale. - Kuang-Huei Lee; Ted Xiao; Adrian Li; Paul Wohlhart; Ian Fischer; Yao Lu 006 (CoRL, 2022)

Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning. - Dhruv Shah; Peng Xu 010; Yao Lu 006; Ted Xiao; Alexander Toshev; Sergey Levine; Brian Ichter (ICLR, 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)

Language to Rewards for Robotic Skill Synthesis. - Wenhao Yu 003; Nimrod Gileadi; Chuyuan Fu; Sean Kirmani; Kuang-Huei Lee; Montserrat Gonzalez Arenas; Hao-Tien Lewis Chiang; Tom Erez; Leonard Hasenclever; Jan Humplik; Brian Ichter; Ted Xiao; et al. (CoRL, 2023)

Open-World Object Manipulation using Pre-Trained Vision-Language Models. - Austin Stone; Ted Xiao; Yao Lu 006; Keerthana Gopalakrishnan; Kuang-Huei Lee; Quan Vuong; Paul Wohlhart; Sean Kirmani; Brianna Zitkovich; Fei Xia 002; Chelsea Finn; Karol Hausman (CoRL, 2023)

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)

Token Turing Machines. - Michael S. Ryoo; Keerthana Gopalakrishnan; Kumara Kahatapitiya; Ted Xiao; Kanishka Rao; Austin Stone; Yao Lu 006; Julian Ibarz; Anurag Arnab (CVPR, 2023)

Jump-Start Reinforcement Learning. - Ikechukwu Uchendu; Ted Xiao; Yao Lu 006; Banghua Zhu; Mengyuan Yan; Joséphine Simon; Matthew Bennice; Chuyuan Fu; Cong Ma 001; Jiantao Jiao; Sergey Levine; Karol Hausman (ICML, 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)

Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models. - Ted Xiao; Harris Chan; Pierre Sermanet; Ayzaan Wahid; Anthony Brohan; Karol Hausman; Sergey Levine; Jonathan Tompson (Robotics: Science and Systems, 2023)

Scaling Robot Learning with Semantically Imagined Experience. - Tianhe Yu; Ted Xiao; Jonathan Tompson; Austin Stone; Su Wang; Anthony Brohan; Jaspiar Singh; Clayton Tan; Dee M; Jodilyn Peralta; Karol Hausman; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Demonstrating Large Language Models on Robots. - Andy Zeng 001; Brian Ichter; Fei Xia 002; Ted Xiao; Vikas Sindhwani (Robotics: Science and Systems, 2023)

Open-World Object Manipulation using Pre-trained Vision-Language Models. - Austin Stone; Ted Xiao; Yao Lu 006; Keerthana Gopalakrishnan; Kuang-Huei Lee; Quan Vuong; Paul Wohlhart; Brianna Zitkovich; Fei Xia 002; Chelsea Finn; Karol Hausman (CoRR, 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)

OpenVLA: An Open-Source Vision-Language-Action Model. - Moo Jin Kim; Karl Pertsch; Siddharth Karamcheti; Ted Xiao; Ashwin Balakrishna; Suraj Nair 003; Rafael Rafailov; Ethan Paul Foster; Pannag R. Sanketi; Quan Vuong; Thomas Kollar; Benjamin Burchfiel; et al. (CoRL, 2024)

Evaluating Real-World Robot Manipulation Policies in Simulation. - Xuanlin Li; Kyle Hsu; Jiayuan Gu; Oier Mees; Karl Pertsch; Homer Rich Walke; Chuyuan Fu; Ishikaa Lunawat; Isabel Sieh; Sean Kirmani; Sergey Levine; Jiajun Wu 001; et al. (CoRL, 2024)

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches. - Priya Sundaresan; Quan Vuong; Jiayuan Gu; Peng Xu 010; Ted Xiao; Sean Kirmani; Tianhe Yu; Michael Stark 003; Ajinkya Jain; Karol Hausman; Dorsa Sadigh; Jeannette Bohg; et al. (CoRL, 2024)

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches. - Jiayuan Gu; Sean Kirmani; Paul Wohlhart; Yao Lu 006; Montserrat Gonzalez Arenas; Kanishka Rao; Wenhao Yu 003; Chuyuan Fu; Keerthana Gopalakrishnan; Zhuo Xu; Priya Sundaresan; Peng Xu 010; et al. (ICLR, 2024)

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. - Jesse Farebrother; Jordi Orbay; Quan Vuong; Adrien Ali Taïga; Yevgen Chebotar; Ted Xiao; Alex Irpan; Sergey Levine; Pablo Samuel Castro; Aleksandra Faust; Aviral Kumar; Rishabh Agarwal (ICML, 2024)

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs. - Soroush Nasiriany; Fei Xia 002; Wenhao Yu 003; Ted Xiao; Jacky Liang; Ishita Dasgupta 001; Annie Xie; Danny Driess; Ayzaan Wahid; Zhuo Xu; Quan Vuong; Tingnan Zhang; et al. (ICML, 2024)

How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. - Montserrat Gonzalez Arenas; Ted Xiao; Sumeet Singh; Vidhi Jain; Allen Z. Ren; Quan Vuong; Jake Varley; Alexander Herzog; Isabel Leal; Sean Kirmani; Mario Prats; Dorsa Sadigh; et al. (ICRA, 2024)

Physically Grounded Vision-Language Models for Robotic Manipulation. - Jensen Gao; Bidipta Sarkar; Fei Xia 002; Ted Xiao; Jiajun Wu 001; Brian Ichter; Anirudha Majumdar; Dorsa Sadigh (ICRA, 2024)

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)

Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation. - Annie Xie; Lisa Lee; Ted Xiao; Chelsea Finn (ICRA, 2024)

RT-H: Action Hierarchies using Language. - Suneel Belkhale; Tianli Ding; Ted Xiao; Pierre Sermanet; Quan Vuong; Jonathan Tompson; Yevgen Chebotar; Debidatta Dwibedi; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Efficient Data Collection for Robotic Manipulation via Compositional Generalization. - Jensen Gao; Annie Xie; Ted Xiao; Chelsea Finn; Dorsa Sadigh (Robotics: Science and Systems, 2024)

Octo: An Open-Source Generalist Robot Policy. - Dibya Ghosh; Homer Rich Walke; Karl Pertsch; Kevin Black; Oier Mees; Sudeep Dasari; Joey Hejna; Tobias Kreiman; Charles Xu 003; Jianlan Luo; You Liang Tan; Lawrence Yunliang Chen; et al. (Robotics: Science and Systems, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (Robotics: Science and Systems, 2024)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Maria Attarian; Maria Bauzá Villalonga; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Fu; Nimrod Gileadi; Marissa Giustina; et al. (Robotics: Science and Systems, 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)

Learning to Learn Faster from Human Feedback with Language Model Predictive Control. - Jacky Liang; Fei Xia 002; Wenhao Yu 003; Andy Zeng 001; Montserrat Gonzalez Arenas; Maria Attarian; Maria Bauzá 001; Matthew Bennice; Alex Bewley; Adil Dostmohamed; Chuyuan Kelly Fu; Nimrod Gileadi; et al. (CoRR, 2024)

RT-H: Action Hierarchies Using Language. - Suneel Belkhale; Tianli Ding; Ted Xiao; Pierre Sermanet; Quon Vuong; Jonathan Tompson; Yevgen Chebotar; Debidatta Dwibedi; Dorsa Sadigh (CoRR, 2024)

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset. - Alexander Khazatsky; Karl Pertsch; Suraj Nair 003; Ashwin Balakrishna; Sudeep Dasari; Siddharth Karamcheti; Soroush Nasiriany; Mohan Kumar Srirama; Lawrence Yunliang Chen; Kirsty Ellis; Peter David Fagan; Joey Hejna; et al. (CoRR, 2024)

Octo: An Open-Source Generalist Robot Policy. - Octo Model Team; Dibya Ghosh; Homer Walke; Karl Pertsch; Kevin Black; Oier Mees; Sudeep Dasari; Joey Hejna; Tobias Kreiman; Charles Xu 003; Jianlan Luo; You Liang Tan; et al. (CoRR, 2024)

OpenVLA: An Open-Source Vision-Language-Action Model. - Moo Jin Kim; Karl Pertsch; Siddharth Karamcheti; Ted Xiao; Ashwin Balakrishna; Suraj Nair 003; Rafael Rafailov; Ethan Paul Foster; Grace Lam; Pannag Sanketi; Quan Vuong; Thomas Kollar; et al. (CoRR, 2024)

Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation. - Homanga Bharadhwaj; Debidatta Dwibedi; Abhinav Gupta 001; Shubham Tulsiani; Carl Doersch; Ted Xiao; Dhruv Shah; Fei Xia 002; Dorsa Sadigh; Sean Kirmani (CoRR, 2024)

RT-Affordance: Affordances are Versatile Intermediate Representations for Robot Manipulation. - Soroush Nasiriany; Sean Kirmani; Tianli Ding; Laura Smith; Yuke Zhu; Danny Driess; Dorsa Sadigh; Ted Xiao (CoRR, 2024)

STEER: Flexible Robotic Manipulation via Dense Language Grounding. - Laura Smith; Alex Irpan; Montserrat Gonzalez Arenas; Sean Kirmani; Dmitry Kalashnikov; Dhruv Shah; Ted Xiao (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Ayzaan Wahid; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Jonathan Tompson; et al. (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma; Joey Hejna; Chuyuan Fu; Dhruv Shah; Jacky Liang; Zhuo Xu; Sean Kirmani; Peng Xu 010; Danny Driess; Ted Xiao; Osbert Bastani; Dinesh Jayaraman; et al. (ICLR, 2025)

Robo-DM: Data Management For Large Robot Datasets. - Kaiyuan Chen 001; Letian Fu; David Huang; Yanxiang Zhang; Lawrence Yunliang Chen; Huang Huang; Kush Hari; Ashwin Balakrishna; Ted Xiao; Pannag R. Sanketi; John Kubiatowicz; Ken Goldberg (CoRR, 2025)

Autonomous Mario Kart in the Wild: Lessons Learned From the Earth Rover Challenge at IROS 2024 [Competitions]. - Xuesu Xiao; Jie Tan 001; Michael Cho; David Hsu; Dhruv Shah; Joanne Truong; Ted Xiao; Naoki Yokoyama; Wenhao Yu 003; Tingnan Zhang; Zhuo Xu; Santiago Pravisani; et al. (IEEE Robotics Autom. Mag., 2025)