Preprints

VAMOS: A Hierarchical Vision-Language-Action Model for Capability-Modulated and Steerable Navigation
Mateo Guaman Castro, Sidharth Rajagopal, Daniel Gorbatov, Matt Schmittle, Rohan Baijal, Octi Zhang, Rosario Scalise, Sidharth Talia, Emma Romig, Celso de Melo, Abhishek Gupta, and others
arXiv preprint, 2025, Runners-up for Madrona Prize at UW, Oral at Workshop on Generalist Robot Policies in the Wild
The Reality Gap in Robotics: Challenges, Solutions, and Best Practices
Elie Aljalbout, Jiaxu Xing, Angel Romero, Iretiayo Akinola, Caelan Reed Garrett, Eric Heiden, Abhishek Gupta, Tucker Hermans, Yashraj Narang, Dieter Fox, and others
arXiv preprint, 2025
Semantic World Models
Jacob Berg, Chuning Zhu, Yanda Bao, Ishan Durugkar, Abhishek Gupta
arXiv preprint, 2025
Using Non-Expert Data to Robustify Imitation Learning via Offline Reinforcement Learning
Kevin Huang, Rosario Scalise, Cleah Winston, Ayush Agrawal, Yunchu Zhang, Rohan Baijal, Markus Grotz, Byron Boots, Benjamin Burchfiel, Hongkai Dai, Abhishek Gupta, and others
arXiv preprint, 2025
PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies
Jesse Zhang, Marius Memmel, Kevin Kim, Dieter Fox, Jesse Thomason, Fabio Ramos, Erdem Bıyık, Abhishek Gupta, Anqi Li
arXiv preprint, 2025
Human-Assisted Continual Robot Learning with Foundation Models
Meenal Parakh, Alisha Fong, Anthony Simeonov, Abhishek Gupta, Tao Chen, Pulkit Agrawal
Accelerating online reinforcement learning with offline datasets
Ashvin Nair*, Abhishek Gupta*, Murtaza Dalal, Sergey Levine
arXiv preprint, 2020
Ecological Reinforcement Learning
John D Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine
arXiv preprint, 2020
Learning latent state representation for speeding up exploration
Giulia Vezzani, Abhishek Gupta, Lorenzo Natale, Pieter Abbeel
arXiv preprint, 2019
Unsupervised meta-learning for reinforcement learning
Abhishek Gupta*, Benjamin Eysenbach*, Chelsea Finn, Sergey Levine
arXiv preprint, 2018, best paper at LLARLA workshop at ICML 2018

2025

Steering Your Diffusion Policy with Latent Space Reinforcement Learning
Andrew Wagenmaker, Mitsuhiko Nakamoto, Yunchu Zhang, Seohong Park, Waleed Yagoub, Anusha Nagabandi, Abhishek Gupta, Sergey Levine
Conference on Robot Learning (CoRL), 2025 (Oral, Best Paper Nominee)
RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies
Pranav Atreya, Karl Pertsch, Tony Lee, Moo Jin Kim, Arhan Jain, Artur Kuramshin, Clemens Eppner, Cyrus Neary, Edward Hu, Fabio Ramos, Abhishek Gupta, and others
Conference on Robot Learning (CoRL), 2025 (Oral)
ATK: Automatic Task-driven Keypoint Selection for Robust Policy Learning
Yunchu Zhang, Shubham Mittal, Zhengyu Zhang, Liyiming Ke, Siddhartha Srinivasa, Abhishek Gupta
Conference on Robot Learning (CoRL), 2025
Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets
Chuning Zhu, Raymond Yu, Siyuan Feng, Benjamin Burchfiel, Paarth Shah, Abhishek Gupta
Robotics: Science and Systems (RSS), 2025 (Best Paper Award), Best Paper at ICML 2025 Workshop on Building Physically Plausible World Models
DRAWER: Digital Reconstruction and Articulation With Environment Realism
Hongchi Xia, Entong Su, Marius Memmel, Arhan Jain, Raymond Yu, Numfor Mbiziwo-Tiapo, Ali Farhadi, Abhishek Gupta, Shenlong Wang, Wei-Chiu Ma
Conference on Computer Vision and Pattern Recognition (CVPR), 2025
DUOLINGO: Dynamics Utilization for Online Translation of Actions
Karthikeya Vemuri, Alan Wu, Arnav Thareja, Zoey Chen, Ian Good, Jeffrey Lipton, Abhishek Gupta
International Conference on Robotics and Automation (ICRA), 2025
SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks
Yijie Guo, Bingjie Tang, Iretiayo Akinola, Dieter Fox, Abhishek Gupta, Yashraj Narang
International Conference on Learning Representations (ICLR), 2025 (Spotlight)
HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation
Yi Li*, Yuquan Deng*, Jesse Zhang*, Joel Jang, Marius Memmel, Raymond Yu, Caelan Reed Garrett, Fabio Ramos, Dieter Fox, Anqi Li, Abhishek Gupta*, Ankit Goyal*
International Conference on Learning Representations (ICLR), 2025
Rapidly Adapting Policies to the Real-World via Simulation-Guided Fine-Tuning
Patrick Yin*, Tyler Westenbroek*, Simran Bagaria, Kevin Huang, Ching-An Cheng, Andrey Kolobov, Abhishek Gupta
International Conference on Learning Representations (ICLR), 2025
STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning
Marius Memmel*, Jacob Berg*, Bingqing Chen, Abhishek Gupta*, Jonathan Francis*
International Conference on Learning Representations (ICLR), 2025

2024

Robot Learning with Super-Linear Scaling
Marcel Torne, Arhan Jain, Jiayi Yuan, Vidaaranya Macha, Lars Ankile, Anthony Simeonov, Pulkit Agrawal, Abhishek Gupta
arXiv preprint
Learning to Cooperate with Humans using Generative Agents
Yancheng Liang, Daphne Chen, Abhishek Gupta, Simon S. Du, Natasha Jaques
Neural Information Processing Systems (NeurIPS), 2024
Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL
Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Byron Boots, Kevin Jamieson, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2024
Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning
Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, Natasha Jaques
Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)
Distributional Successor Features Enable Zero-Shot Policy Optimization
Chuning Zhu, Xinqi Wang, Tyler Han, Simon S. Du, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2024
Teaching Robots with Show and Tell: Using Foundation Models to Synthesize Robot Policies from Language and Visual Demonstration
Michael Murray, Abhishek Gupta, Maya Cakmak
Conference on Robot Learning (CoRL), 2024
Semantically Controllable Augmentations for Generalizable Robot Learning
Zoey Chen, Zhao Mandi, Homanga Bharadhwaj, Mohit Sharma, Shuran Song, Abhishek Gupta, Vikash Kumar
International Journal of Robotics Research (IJRR), 2024
Data Efficient Behavior Cloning for Fine Manipulation via Continuity-based Corrective Labels
Abhay Deshpande, Liyiming Ke, Quinn Pfeifer, Abhishek Gupta, Siddhartha S. Srinivasa
International Conference on Intelligent Robots and Systems (IROS), 2024
DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset
DROID Collaboration Team
Robotics: Science and Systems (RSS), 2024
Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation
Marcel Torne, Anthony Simeonov, Zechu Li, April Chan, Tao Chen, Abhishek Gupta, Pulkit Agrawal
Robotics: Science and Systems (RSS), 2024
URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images
Zoey Chen, Aaron Walsman, Marius Memmel, Kaichun Mo, Alex Fang, Karthikeya Vemuri, Alan Wu, Dieter Fox, Abhishek Gupta
Robotics: Science and Systems (RSS), 2024
SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning
Jianlan Luo, Zheyuan Hu, Charles Xu, You Liang Tan, Jacob Berg, Archit Sharma, Stefan Schaal, Chelsea Finn, Abhishek Gupta, Sergey Levine
International Conference on Robotics and Automation (ICRA), 2024
Rank2Reward: Learning Shaped Reward Functions from Passive Video
Daniel Yang, Davin Tjia, Jacob Berg, Dima Damen, Pulkit Agrawal, Abhishek Gupta
International Conference on Robotics and Automation (ICRA), 2024
Learning to Grasp in Clutter with Interactive Visual Failure Prediction
Michael Murray, Abhishek Gupta, Maya Cakmak
International Conference on Robotics and Automation (ICRA), 2024
Lifelong Robot Learning with Human Assisted Language Planners
Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs
International Conference on Robotics and Automation (ICRA), 2024
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy
Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs
International Conference on Robotics and Automation (ICRA), 2024 (Finalist for Best Paper Award in Robot Vision)
ASID: Active Exploration for System Identification and Reconstruction in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu, Dieter Fox, Abhishek Gupta
International Conference on Learning Representations (ICLR), 2024
Modeling Boundedly Rational Agents with Latent Inference Budgets
Athul Paul Jacob, Abhishek Gupta, Jacob Andreas
International Conference on Learning Representations (ICLR), 2024
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou, Qiwen Cui, Abhishek Gupta, Simon Shaolei Du
International Conference on Learning Representations (ICLR), 2024
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta
International Conference on Learning Representations (ICLR), 2024

2023

RoboHive: A Unified Framework for Robot Learning
Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Jay Vakil, Abhishek Gupta, Aravind Rajeswaran
Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, 2023
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback
Max Balsells I Pamies, Marcel Torne Villasevil, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta
Conference on Robot Learning (CoRL), 2023
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation
Zheyuan Hu, Aaron Rovinsky, Jianlan Luo, Vikash Kumar, Abhishek Gupta, Sergey Levine
Conference on Robot Learning (CoRL), 2023
Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score Matching
H.J. Terry Suh, Glen Chou, Hongkai Dai, Lujie Yang, Abhishek Gupta, Russ Tedrake
Conference on Robot Learning (CoRL), 2023
Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback
Marcel Torne, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal
Neural Information Processing Systems (NeurIPS), 2023
Self-Supervised Reinforcement Learning that Transfers using Random Features
Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2023
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
Chuning Zhu, Max Simchowitz, Siri Gadipudi, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2023 (Spotlight)
Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective
Max Simchowitz, Abhishek Gupta, Kaiqing Zhang
Conference on Learning Theory (COLT), 2023
Guiding Pretraining in Reinforcement Learning with Large Language Models
Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas
International Conference on Machine Learning (ICML), 2023
GenAug: Retargeting behaviors to unseen situations via Generative Augmentation
Zoey Chen, Sho Kiami, Abhishek Gupta*, Vikash Kumar*
Robotics: Science and Systems (RSS), 2023 (Best Systems Paper Finalist)
Cherry-picking with reinforcement learning
Yunchu Zhang, Liyiming Ke, Abhay Deshpande, Abhishek Gupta, Siddhartha Srinivasa
Robotics: Science and Systems (RSS), 2023
Learning to Extrapolate: A Transductive Approach
Aviv Netanyahu*, Abhishek Gupta*, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal
International Conference on Learning Representations (ICLR), 2023
TactoFind: A Tactile Only System for Object Retrieval
Sameer Pai, Tao Chen, Megha Tippur, Edward Adelson, Abhishek Gupta*, Pulkit Agrawal*
International Conference on Robotics and Automation (ICRA), 2023
Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning
Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman
International Conference on Robotics and Automation (ICRA), 2023
Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance
Kelvin Xu*, Zheyuan Hu*, Ria Doshi, Aaron Rovinsky, Vikash Kumar, Abhishek Gupta, Sergey Levine
International Conference on Robotics and Automation (ICRA), 2023

2022

Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation
Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, Dieter Fox
Conference on Robot Learning (CoRL), 2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity
Abhishek Gupta*, Aldo Pacchiano*, Simon Zhai, Sham Kakade, Sergey Levine
Neural Information Processing Systems (NeurIPS), 2022
Distributionally Adaptive Meta Reinforcement Learning
Anurag Ajay*, Abhishek Gupta*, Dibya Ghosh, Sergey Levine, Pulkit Agrawal
Neural Information Processing Systems (NeurIPS), 2022
Autonomous Reinforcement Learning: Formalism and Benchmarking
Archit Sharma*, Kelvin Xu*, Nikhil Sardana, Abhishek Gupta, Karol Hausman, Sergey Levine, Chelsea Finn
International Conference on Learning Representations (ICLR), 2022

2021

Teachable Reinforcement Learning via Advice Distillation
Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta
Neural Information Processing Systems (NeurIPS), 2021
Persistent Reinforcement Learning via Subgoal Curricula
Archit Sharma, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
Neural Information Processing Systems (NeurIPS), 2021
Adaptive risk minimization: A meta-learning approach for tackling group shift
Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn
Neural Information Processing Systems (NeurIPS), 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control?
Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine
Neural Information Processing Systems (NeurIPS), 2021
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning
Kevin Li*, Abhishek Gupta*, Ashwin D Reddy, Vitchyr Pong, Aurick Zhou, Justin Yu, Sergey Levine
International Conference on Machine Learning (ICML), 2021
Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention
Abhishek Gupta*, Justin Yu*, Tony Z. Zhao*, Vikash Kumar*, Aaron Rovinsky, Kelvin Xu, Thomas Devlin, Sergey Levine
International Conference on Robotics and Automation (ICRA), 2021
Fully Autonomous Real-World Reinforcement Learning for Mobile Manipulation
Charles Sun, Jedrzej Orbik, Coline Devin, Brian Yang, Abhishek Gupta, Glen Berseth, Sergey Levine
Conference on Robot Learning (CoRL), 2021
Learning to reach goals via iterated supervised learning
Dibya Ghosh*, Abhishek Gupta*, Ashwin Reddy, Justin Fu, Coline Devin, Benjamin Eysenbach, Sergey Levine
International Conference on Learning Representations (ICLR), 2021 (Oral)

2020

The ingredients of real-world robotic reinforcement learning
Henry Zhu*, Justin Yu*, Abhishek Gupta*, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine
International Conference on Learning Representations (ICLR), 2020 (spotlight)
Discor: Corrective feedback in reinforcement learning via distribution correction
Aviral Kumar, Abhishek Gupta, Sergey Levine
Neural Information Processing Systems (NeurIPS), 2020 (spotlight)
Gradient surgery for multi-task learning
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, Chelsea Finn
Neural Information Processing Systems (NeurIPS), 2020

2019

Unsupervised curricula for visual meta-reinforcement learning
Allan Jabri, Kyle Hsu, Benjamin Eysenbach, Abhishek Gupta, Alexei Efros, Sergey Levine, Chelsea Finn
Neural Information Processing Systems (NeurIPS), 2019 (spotlight)
ROBEL: RObotics BEnchmarks for Learning with low-cost robots
Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar
Conference on Robot Learning (CoRL), 2019
Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning
Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, Karol Hausman
Conference on Robot Learning (CoRL), 2019
Guided meta-policy search
Russell Mendonca, Abhishek Gupta, Rosen Kralev, Pieter Abbeel, Sergey Levine, Chelsea Finn
Neural Information Processing Systems (NeurIPS), 2019 (spotlight)
Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost
Henry Zhu*, Abhishek Gupta*, Aravind Rajeswaran, Sergey Levine, Vikash Kumar
International Conference on Robotics and Automation (ICRA), 2019
Diversity is all you need: Learning skills without a reward function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
International Conference on Learning Representations (ICLR), 2019
Guiding policies with language via meta-learning
John D Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, John DeNero, Pieter Abbeel, Sergey Levine
International Conference on Learning Representations (ICLR), 2019
Learning actionable representations with goal-conditioned policies
Dibya Ghosh, Abhishek Gupta, Sergey Levine
International Conference on Learning Representations (ICLR), 2019
Automatically composing representation transformations as a means for generalization
Michael B. Chang, Abhishek Gupta, Sergey Levine, Thomas Griffith
International Conference on Learning Representations (ICLR), 2019

2018

Self-consistent trajectory autoencoder: Hierarchical reinforcement learning with trajectory embeddings
John D Co-Reyes*, YuXuan Liu*, Abhishek Gupta*, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
International Conference on Machine Learning (ICML), 2018
Imitation from observation: Learning to imitate behaviors from raw video via context translation
YuXuan Liu*, Abhishek Gupta*, Pieter Abbeel, Sergey Levine
International Conference on Robotics and Automation (ICRA), 2018
Meta-reinforcement learning of structured exploration strategies
Abhishek Gupta, Russell Mendonca, YuXuan Liu, Pieter Abbeel, Sergey Levine
Neural Information Processing Systems (NeurIPS), 2018 (spotlight)
Learning complex dexterous manipulation with deep reinforcement learning and demonstrations
Aravind Rajeswaran*, Vikash Kumar*, Abhishek Gupta, Giulia Vezzanni, John Schulman, Emanuel Todorov, Sergey Levine
Robotics Science and Systems (RSS), 2018

2017

Learning modular neural network policies for multi-task and multi-robot transfer
Abhishek Gupta*, Coline Devin*, Trevor Darrell, Pieter Abbeel, Sergey Levine
International Conference on Robotics and Automation (ICRA), 2017
Learning invariant feature spaces to transfer skills with reinforcement learning
Abhishek Gupta*, Coline Devin*, Yuxuan Liu, Pieter Abbeel, Sergey Levine
International Conference on Learning Representations (ICLR), 2017

2016

Learning dexterous manipulation for a soft robotic hand from human demonstrations
Abhishek Gupta, Clemens Eppner, Sergey Levine, Pieter Abbeel
International Conference on Intelligent Robots and Systems (IROS), 2016
Guided search for task and motion plans using learned heuristics
Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddhart Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel
International Conference on Robotics and Automation (ICRA), 2016

2015

Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation
Alex Lee, Abhishek Gupta, Henry Lu, Sergey Levine, Pieter Abbeel
International Conference on Intelligent Robots and Systems (IROS), 2015
Learning force-based manipulation of deformable objects from multiple demonstrations
Alex X. Lee, Henry Lu, Abhishek Gupta, Sergey Levine, Pieter Abbeel
International Conference on Robotics and Automation (ICRA), 2015
Tractability of planning with loops
Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell
AAAI Conference on Artificial Intelligence (AAAI), 2015