Diverse Sampling for Normalizing Flow Based Trajectory Forecasting. - Yecheng Jason Ma 001; Jeevana Priya Inala; Dinesh Jayaraman; Osbert Bastani (CoRR, 2020)

Likelihood-Based Diverse Sampling for Trajectory Forecasting. - Yecheng Jason Ma 001; Jeevana Priya Inala; Dinesh Jayaraman; Osbert Bastani (ICCV, 2021)

State Relevance for Off-Policy Evaluation. - Simon P. Shen; Yecheng Jason Ma 001; Omer Gottesman; Finale Doshi-Velez (ICML, 2021)

Conservative Offline Distributional Reinforcement Learning. - Yecheng Jason Ma 001; Dinesh Jayaraman; Osbert Bastani (NeurIPS, 2021)

Safe Human-Interactive Control via Shielding. - Jeevana Priya Inala; Yecheng Jason Ma 001; Osbert Bastani; Xin Zhang 035; Armando Solar-Lezama (CoRR, 2021)

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning. - Yecheng Jason Ma 001; Andrew Shen; Osbert Bastani; Dinesh Jayaraman (AAAI, 2022)

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching. - Yecheng Jason Ma 001; Andrew Shen; Dinesh Jayaraman; Osbert Bastani (ICML, 2022)

Regret Bounds for Risk-Sensitive Reinforcement Learning. - Osbert Bastani; Yecheng Jason Ma 001; Estelle Shen; Wanqiao Xu (NeurIPS, 2022)

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression. - Yecheng Jason Ma 001; Jason Yan; Dinesh Jayaraman; Osbert Bastani (NeurIPS, 2022)

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching. - Yecheng Jason Ma 001; Andrew Shen; Dinesh Jayaraman; Osbert Bastani (CoRR, 2022)

How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression. - Yecheng Jason Ma 001; Jason Yan; Dinesh Jayaraman; Osbert Bastani (CoRR, 2022)

Uniformly Conservative Exploration in Reinforcement Learning. - Wanqiao Xu; Yecheng Jason Ma 001; Kan Xu; Hamsa Bastani; Osbert Bastani (AISTATS, 2023)

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training. - Yecheng Jason Ma 001; Shagun Sodhani; Dinesh Jayaraman; Osbert Bastani; Vikash Kumar; Amy Zhang 001 (ICLR, 2023)

LIV: Language-Image Representations and Rewards for Robotic Control. - Yecheng Jason Ma 001; Vikash Kumar; Amy Zhang 001; Osbert Bastani; Dinesh Jayaraman (ICML, 2023)

Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. - Yecheng Jason Ma 001; Kausik Sivakumar; Jason Yan; Osbert Bastani; Dinesh Jayaraman (L4DC, 2023)

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? - Arjun Majumdar; Karmesh Yadav; Sergio Arnaud; Yecheng Jason Ma 001; Claire Chen; Sneha Silwal; Aryan Jain; Vincent-Pierre Berges; Tingfan Wu; Jay Vakil; Pieter Abbeel; Jitendra Malik; et al. (NeurIPS, 2023)

Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? - Arjun Majumdar; Karmesh Yadav; Sergio Arnaud; Yecheng Jason Ma 001; Claire Chen; Sneha Silwal; Aryan Jain; Vincent-Pierre Berges; Pieter Abbeel; Jitendra Malik; Dhruv Batra; Yixin Lin; et al. (CoRR, 2023)

TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching. - Yecheng Jason Ma 001; Kausik Sivakumar; Jason Yan; Osbert Bastani; Dinesh Jayaraman (CoRR, 2023)

LIV: Language-Image Representations and Rewards for Robotic Control. - Yecheng Jason Ma 001; William Liang; Vaidehi Som; Vikash Kumar; Amy Zhang 001; Osbert Bastani; Dinesh Jayaraman (CoRR, 2023)

Environment Curriculum Generation via Large Language Models. - William Liang; Sam Wang; Hung-Ju Wang; Osbert Bastani; Dinesh Jayaraman; Yecheng Jason Ma 001 (CoRL, 2024)

Eureka: Human-Level Reward Design via Coding Large Language Models. - Yecheng Jason Ma 001; William Liang; Guanzhi Wang; De-An Huang; Osbert Bastani; Dinesh Jayaraman; Yuke Zhu; Linxi Fan; Anima Anandkumar (ICLR, 2024)

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy. - Zichen Zhang 016; Yunshuang Li; Osbert Bastani; Abhishek Gupta 004; Dinesh Jayaraman; Yecheng Jason Ma 001; Luca Weihs (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)

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models. - Junyao Shi; Jianing Qian; Yecheng Jason Ma 001; Dinesh Jayaraman (ICRA, 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)

DrEureka: Language Model Guided Sim-To-Real Transfer. - Yecheng Jason Ma 001; William Liang; Hung-Ju Wang; Yuke Zhu; Linxi Fan; Osbert Bastani; Dinesh Jayaraman (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. (CoRR, 2024)

DrEureka: Language Model Guided Sim-To-Real Transfer. - Yecheng Jason Ma 001; William Liang; Hung-Ju Wang; Sam Wang; Yuke Zhu; Linxi Fan; Osbert Bastani; Dinesh Jayaraman (CoRR, 2024)

Eurekaverse: Environment Curriculum Generation via Large Language Models. - William Liang; Sam Wang; Hung-Ju Wang; Osbert Bastani; Dinesh Jayaraman; Yecheng Jason Ma 001 (CoRR, 2024)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma 001; 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)

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model. - Long Le; Jason Xie; William Liang; Hung-Ju Wang; Yue Yang; Yecheng Jason Ma 001; Kyle Vedder; Arjun Krishna; Dinesh Jayaraman; Eric Eaton (ICLR, 2025)

Vision Language Models are In-Context Value Learners. - Yecheng Jason Ma 001; 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)

On-Robot Reinforcement Learning with Goal-Contrastive Rewards. - Ondrej Biza; Thomas Weng; Lingfeng Sun; Karl Schmeckpeper; Tarik Kelestemur; Yecheng Jason Ma 001; Robert Platt 001; Jan-Willem van de Meent; Lawson L. S. Wong (ICRA, 2025)

ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos. - Junyao Shi; Zhuolun Zhao; Tianyou Wang; Ian Pedroza; Amy Luo; Jie Wang; Jason Ma 001; Dinesh Jayaraman (ICRA, 2025)