Tractability of Planning with Loops. - Siddharth Srivastava 001; Shlomo Zilberstein; Abhishek Gupta 004; Pieter Abbeel; Stuart Russell 001 (AAAI, 2015)

Learning force-based manipulation of deformable objects from multiple demonstrations. - Alex X. Lee; Henry Lu; Abhishek Gupta 004; Sergey Levine; Pieter Abbeel (ICRA, 2015)

Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation. - Alex X. Lee; Abhishek Gupta 004; Henry Lu; Sergey Levine; Pieter Abbeel (IROS, 2015)

Guided search for task and motion plans using learned heuristics. - Rohan Chitnis; Dylan Hadfield-Menell; Abhishek Gupta 004; Siddharth Srivastava 001; Edward Groshev; Christopher Lin; Pieter Abbeel (ICRA, 2016)

Learning dexterous manipulation for a soft robotic hand from human demonstrations. - Abhishek Gupta 004; Clemens Eppner; Sergey Levine; Pieter Abbeel (IROS, 2016)

Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration. - Abhishek Gupta 004; Clemens Eppner; Sergey Levine; Pieter Abbeel (CoRR, 2016)

Learning Dexterous Manipulation Policies from Experience and Imitation. - Vikash Kumar; Abhishek Gupta 004; Emanuel Todorov; Sergey Levine (CoRR, 2016)

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning. - Abhishek Gupta 004; Coline Devin; Yuxuan Liu 001; Pieter Abbeel; Sergey Levine (ICLR (Poster), 2017)

Learning modular neural network policies for multi-task and multi-robot transfer. - Coline Devin; Abhishek Gupta 004; Trevor Darrell; Pieter Abbeel; Sergey Levine (ICRA, 2017)

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. - Aravind Rajeswaran; Vikash Kumar; Abhishek Gupta 004; John Schulman; Emanuel Todorov; Sergey Levine (CoRR, 2017)

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. - John D. Co-Reyes; Yuxuan Liu 001; Abhishek Gupta 004; Benjamin Eysenbach; Pieter Abbeel; Sergey Levine (ICML, 2018)

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation. - Yuxuan Liu 001; Abhishek Gupta 004; Pieter Abbeel; Sergey Levine (ICRA, 2018)

Meta-Reinforcement Learning of Structured Exploration Strategies. - Abhishek Gupta 004; Russell Mendonca; Yuxuan Liu 001; Pieter Abbeel; Sergey Levine (NeurIPS, 2018)

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. - Aravind Rajeswaran; Vikash Kumar; Abhishek Gupta 004; Giulia Vezzani; John Schulman; Emanuel Todorov; Sergey Levine (Robotics: Science and Systems, 2018)

Unsupervised Meta-Learning for Reinforcement Learning. - Abhishek Gupta 004; Benjamin Eysenbach; Chelsea Finn; Sergey Levine (CoRR, 2018)

Guiding Policies with Language via Meta-Learning. - John D. Co-Reyes; Abhishek Gupta 004; Suvansh Sanjeev; Nick Altieri 001; John DeNero; Pieter Abbeel; Sergey Levine (CoRR, 2018)

Soft Actor-Critic Algorithms and Applications. - Tuomas Haarnoja; Aurick Zhou; Kristian Hartikainen; George Tucker; Sehoon Ha; Jie Tan 001; Vikash Kumar; Henry Zhu; Abhishek Gupta 004; Pieter Abbeel; Sergey Levine (CoRR, 2018)

Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning. - Abhishek Gupta 004; Vikash Kumar; Corey Lynch; Sergey Levine; Karol Hausman (CoRL, 2019)

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots. - Michael Ahn; Henry Zhu; Kristian Hartikainen; Hugo Ponte; Abhishek Gupta 004; Sergey Levine; Vikash Kumar (CoRL, 2019)

Automatically Composing Representation Transformations as a Means for Generalization. - Michael Chang 003; Abhishek Gupta 004; Sergey Levine; Thomas L. Griffiths 001 (ICLR (Poster), 2019)

Guiding Policies with Language via Meta-Learning. - John D. Co-Reyes; Abhishek Gupta 004; Suvansh Sanjeev; Nick Altieri 001; Jacob Andreas; John DeNero; Pieter Abbeel; Sergey Levine (ICLR (Poster), 2019)

Diversity is All You Need: Learning Skills without a Reward Function. - Benjamin Eysenbach; Abhishek Gupta 004; Julian Ibarz; Sergey Levine (ICLR (Poster), 2019)

Learning Actionable Representations with Goal Conditioned Policies. - Dibya Ghosh; Abhishek Gupta 004; Sergey Levine (ICLR (Poster), 2019)

Domain Randomization for Active Pose Estimation. - Xinyi Ren; Jianlan Luo; Eugen Solowjow; Juan Aparicio Ojea; Abhishek Gupta 004; Aviv Tamar; Pieter Abbeel (ICRA, 2019)

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. - Henry Zhu; Abhishek Gupta 004; Aravind Rajeswaran; Sergey Levine; Vikash Kumar (ICRA, 2019)

Unsupervised Curricula for Visual Meta-Reinforcement Learning. - Allan Jabri; Kyle Hsu; Abhishek Gupta 004; Ben Eysenbach; Sergey Levine; Chelsea Finn (NeurIPS, 2019)

Guided Meta-Policy Search. - Russell Mendonca; Abhishek Gupta 004; Rosen Kralev; Pieter Abbeel; Sergey Levine; Chelsea Finn (NeurIPS, 2019)

Learning latent state representation for speeding up exploration. - Giulia Vezzani; Abhishek Gupta 004; Lorenzo Natale; Pieter Abbeel (CoRR, 2019)

Learning To Reach Goals Without Reinforcement Learning. - Dibya Ghosh; Abhishek Gupta 004; Justin Fu; Ashwin Reddy; Coline Devin; Benjamin Eysenbach; Sergey Levine (CoRR, 2019)

The Ingredients of Real World Robotic Reinforcement Learning. - Henry Zhu; Justin Yu; Abhishek Gupta 004; Dhruv Shah; Kristian Hartikainen; Avi Singh; Vikash Kumar; Sergey Levine (ICLR, 2020)

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. - Aviral Kumar; Abhishek Gupta 004; Sergey Levine (NeurIPS, 2020)

Gradient Surgery for Multi-Task Learning. - Tianhe Yu; Saurabh Kumar 004; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2020)

Accelerating Online Reinforcement Learning with Offline Datasets. - Ashvin Nair; Murtaza Dalal; Abhishek Gupta 004; Sergey Levine (CoRR, 2020)

Ecological Reinforcement Learning. - John D. Co-Reyes; Suvansh Sanjeev; Glen Berseth; Abhishek Gupta 004; Sergey Levine (CoRR, 2020)

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift. - Marvin Zhang; Henrik Marklund; Abhishek Gupta 004; Sergey Levine; Chelsea Finn (CoRR, 2020)

Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation. - Charles Sun; Jedrzej Orbik; Coline Manon Devin; Brian H. Yang; Abhishek Gupta 004; Glen Berseth; Sergey Levine (CoRL, 2021)

Learning to Reach Goals via Iterated Supervised Learning. - Dibya Ghosh; Abhishek Gupta 004; Ashwin Reddy; Justin Fu; Coline Manon Devin; Benjamin Eysenbach; Sergey Levine (ICLR, 2021)

MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. - Kevin Li; Abhishek Gupta 004; Ashwin Reddy; Vitchyr H. Pong; Aurick Zhou; Justin Yu; Sergey Levine (ICML, 2021)

Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Intervention. - Abhishek Gupta 004; Justin Yu; Tony Z. Zhao; Vikash Kumar; Aaron Rovinsky; Kelvin Xu; Thomas Devlin; Sergey Levine (ICRA, 2021)

Which Mutual-Information Representation Learning Objectives are Sufficient for Control? - Kate Rakelly; Abhishek Gupta 004; Carlos Florensa; Sergey Levine (NeurIPS, 2021)

Autonomous Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2021)

Teachable Reinforcement Learning via Advice Distillation. - Olivia Watkins; Abhishek Gupta 004; Trevor Darrell; Pieter Abbeel; Jacob Andreas (NeurIPS, 2021)

Adaptive Risk Minimization: Learning to Adapt to Domain Shift. - Marvin Zhang; Henrik Marklund; Nikita Dhawan; Abhishek Gupta 004; Sergey Levine; Chelsea Finn (NeurIPS, 2021)

Persistent Reinforcement Learning via Subgoal Curricula. - Archit Sharma; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (CoRR, 2021)

ReLMM: Practical RL for Learning Mobile Manipulation Skills Using Only Onboard Sensors. - Charles Sun; Jedrzej Orbik; Coline Devin; Brian H. Yang; Abhishek Gupta 004; Glen Berseth; Sergey Levine (CoRR, 2021)

How to Train Your Robot: Techniques for Enabling Robotic Learning in the Real World - Abhishek Gupta 004 (2021)

Learning Robust Real-World Dexterous Grasping Policies via Implicit Shape Augmentation. - Zoey Qiuyu Chen; Karl Van Wyk; Yu-Wei Chao; Wei Yang 019; Arsalan Mousavian; Abhishek Gupta 004; Dieter Fox (CoRL, 2022)

Autonomous Reinforcement Learning: Formalism and Benchmarking. - Archit Sharma; Kelvin Xu; Nikhil Sardana; Abhishek Gupta 004; Karol Hausman; Sergey Levine; Chelsea Finn (ICLR, 2022)

Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity. - Abhishek Gupta 004; Aldo Pacchiano; Yuexiang Zhai; Sham M. Kakade; Sergey Levine (NeurIPS, 2022)

Distributionally Adaptive Meta Reinforcement Learning. - Anurag Ajay; Abhishek Gupta 004; Dibya Ghosh; Sergey Levine; Pulkit Agrawal 001 (NeurIPS, 2022)

DexTransfer: Real World Multi-fingered Dexterous Grasping with Minimal Human Demonstrations. - Zoey Qiuyu Chen; Karl Van Wyk; Yu-Wei Chao; Wei Yang 019; Arsalan Mousavian; Abhishek Gupta 004; Dieter Fox (CoRR, 2022)

Tackling Combinatorial Distribution Shift: A Matrix Completion Perspective. - Max Simchowitz; Abhishek Gupta 004; Kaiqing Zhang (COLT, 2023)

Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback. - Max Balsells; Marcel Torne Villasevil; Zihan Wang; Samedh Desai; Pulkit Agrawal 001; Abhishek Gupta 004 (CoRL, 2023)

REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation. - Zheyuan Hu 003; Aaron Rovinsky; Jianlan Luo; Vikash Kumar; Abhishek Gupta 004; Sergey Levine (CoRL, 2023)

Learning to Extrapolate: A Transductive Approach. - Aviv Netanyahu; Abhishek Gupta 004; Max Simchowitz; Kaiqing Zhang; Pulkit Agrawal 001 (ICLR, 2023)

Guiding Pretraining in Reinforcement Learning with Large Language Models. - Yuqing Du; Olivia Watkins; Zihan Wang; Cédric Colas; Trevor Darrell; Pieter Abbeel; Abhishek Gupta 004; Jacob Andreas (ICML, 2023)

Demonstration-Bootstrapped Autonomous Practicing via Multi-Task Reinforcement Learning. - Abhishek Gupta 004; Corey Lynch; Brandon Kinman; Garrett Peake; Sergey Levine; Karol Hausman (ICRA, 2023)

TactoFind: A Tactile Only System for Object Retrieval. - Sameer Pai; Tao Chen 046; Megha Tippur; Edward H. Adelson; Abhishek Gupta 004; Pulkit Agrawal 001 (ICRA, 2023)

Dexterous Manipulation from Images: Autonomous Real-World RL via Substep Guidance. - Kelvin Xu; Zheyuan Hu 003; Ria Doshi; Aaron Rovinsky; Vikash Kumar; Abhishek Gupta 004; Sergey Levine (ICRA, 2023)

Self-Supervised Reinforcement Learning that Transfers using Random Features. - Boyuan Chen 003; Chuning Zhu; Pulkit Agrawal 001; Kaiqing Zhang; Abhishek Gupta 004 (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 004; Pulkit Agrawal 001 (NeurIPS, 2023)

RoboHive: A Unified Framework for Robot Learning. - Vikash Kumar; Rutav M. Shah; Gaoyue Zhou; Vincent Moens; Vittorio Caggiano; Abhishek Gupta 004; Aravind Rajeswaran (NeurIPS, 2023)

Breadcrumbs to the Goal: Supervised Goal Selection from Human-in-the-Loop Feedback. - Marcel Torne Villasevil; Max Balsells; Zihan Wang; Samedh Desai; Tao Chen 046; Pulkit Agrawal 001; Abhishek Gupta 004 (NeurIPS, 2023)

RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability. - Chuning Zhu; Max Simchowitz; Siri Gadipudi; Abhishek Gupta 004 (NeurIPS, 2023)

GenAug: Retargeting behaviors to unseen situations via Generative Augmentation. - Zoey Qiuyu Chen; Shosuke C. Kiami; Abhishek Gupta 004; Vikash Kumar (Robotics: Science and Systems, 2023)

Cherry-Picking with Reinforcement Learning. - Yunchu Zhang; Liyiming Ke; Abhay Deshpande; Abhishek Gupta 004; Siddhartha S. Srinivasa (Robotics: Science and Systems, 2023)

Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback. - Marcel Torne; Max Balsells; Zihan Wang; Samedh Desai; Tao Chen 046; Pulkit Agrawal 001; Abhishek Gupta 004 (CoRR, 2023)

Human-Assisted Continual Robot Learning with Foundation Models. - Meenal Parakh; Alisha Fong; Anthony Simeonov; Abhishek Gupta 004; Tao Chen 046; Pulkit Agrawal 001 (CoRR, 2023)

RoboHive: A Unified Framework for Robot Learning. - Vikash Kumar; Rutav M. Shah; Gaoyue Zhou; Vincent Moens; Vittorio Caggiano; Jay Vakil; Abhishek Gupta 004; Aravind Rajeswaran (CoRR, 2023)

Modeling Boundedly Rational Agents with Latent Inference Budgets. - Athul Paul Jacob; Abhishek Gupta 004; Jacob Andreas (ICLR, 2024)

CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning. - Liyiming Ke; Yunchu Zhang; Abhay Deshpande; Siddhartha S. Srinivasa; Abhishek Gupta 004 (ICLR, 2024)

ASID: Active Exploration for System Identification in Robotic Manipulation. - Marius Memmel; Andrew Wagenmaker; Chuning Zhu; Dieter Fox; Abhishek Gupta 004 (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 004; Simon Shaolei Du (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; Luca Weihs (ICRA, 2024)

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning. - Jianlan Luo; Zheyuan Hu 003; Charles Xu 003; You Liang Tan; Jacob Berg; Archit Sharma; Stefan Schaal; Chelsea Finn; Abhishek Gupta 004; Sergey Levine (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)

Lifelong Robot Learning with Human Assisted Language Planners. - Meenal Parakh; Alisha Fong; Anthony Simeonov; Tao Chen 046; Abhishek Gupta 004; Pulkit Agrawal 001 (ICRA, 2024)

Rank2Reward: Learning Shaped Reward Functions from Passive Video. - Daniel Yang; Davin Tjia; Jacob Berg; Dima Damen; Pulkit Agrawal 001; Abhishek Gupta 004 (ICRA, 2024)

Data Efficient Behavior Cloning for Fine Manipulation via Continuity-based Corrective Labels. - Abhay Deshpande; Liyiming Ke; Quinn Pfeifer; Abhishek Gupta 004; Siddhartha S. Srinivasa (IROS, 2024)

Learning to Cooperate with Humans using Generative Agents. - Yancheng Liang; Daphne Chen; Abhishek Gupta 004; Simon S. Du; Natasha Jaques (NeurIPS, 2024)

Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL. - Andrew Wagenmaker; Kevin Huang; Liyiming Ke; Kevin G. Jamieson; Abhishek Gupta 004 (NeurIPS, 2024)

Distributional Successor Features Enable Zero-Shot Policy Optimization. - Chuning Zhu; Xinqi Wang; Tyler Han; Simon S. Du; Abhishek Gupta 004 (NeurIPS, 2024)

URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images. - Qiuyu Chen; Aaron Walsman; Marius Memmel; Kaichun Mo; Alex Fang; Dieter Fox; Abhishek Gupta 004 (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)

Reconciling Reality through Simulation: A Real-To-Sim-to-Real Approach for Robust Manipulation. - Marcel Torne Villasevil; Anthony Simeonov; Zechu Li; April Chan; Tao Chen 046; Abhishek Gupta 004; Pulkit Agrawal 001 (Robotics: Science and Systems, 2024)

Transferable Reinforcement Learning via Generalized Occupancy Models. - Chuning Zhu; Xinqi Wang; Tyler Han; Simon S. Du; Abhishek Gupta 004 (CoRR, 2024)

ASID: Active Exploration for System Identification in Robotic Manipulation. - Marius Memmel; Andrew Wagenmaker; Chuning Zhu; Patrick Yin; Dieter Fox; Abhishek Gupta 004 (CoRR, 2024)

URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images. - Zoey Qiuyu Chen; Aaron Walsman; Marius Memmel; Kaichun Mo; Alex Fang; Karthikeya Vemuri; Alan Wu; Dieter Fox; Abhishek Gupta 004 (CoRR, 2024)

Semantically Controllable Augmentations for Generalizable Robot Learning. - Zoey Qiuyu Chen; Zhao Mandi; Homanga Bharadhwaj; Mohit Sharma 001; Shuran Song; Abhishek Gupta 004; Vikash Kumar (CoRR, 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 G. Jamieson; Abhishek Gupta 004 (CoRR, 2024)

Robot Learning with Super-Linear Scaling. - Marcel Torne; Arhan Jain; Jiayi Yuan 002; Vidaaranya Macha; Lars Ankile; Anthony Simeonov; Pulkit Agrawal 001; Abhishek Gupta 004 (CoRR, 2024)

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 004; Shenlong Wang; Wei-Chiu Ma (CVPR, 2025)

HAMSTER: Hierarchical Action Models for Open-World Robot Manipulation. - Yi Li 038; Yuquan Deng; Jesse Zhang; Joel Jang; Marius Memmel; Caelan Reed Garrett; Fabio Ramos 001; Dieter Fox; Anqi Li 001; Abhishek Gupta 004; Ankit Goyal 001 (ICLR, 2025)

SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks. - Yijie Guo; Bingjie Tang; Iretiayo Akinola; Dieter Fox; Abhishek Gupta 004; Yashraj Narang (ICLR, 2025)

STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning. - Marius Memmel; Jacob Berg; Bingqing Chen; Abhishek Gupta 004; Jonathan Francis (ICLR, 2025)

HAMSTER: Hierarchical Action Models For Open-World Robot Manipulation. - Yi Li 038; Yuquan Deng; Jesse Zhang; Joel Jang; Marius Memmel; Raymond Yu; Caelan Reed Garrett; Fabio Ramos 001; Dieter Fox; Anqi Li 001; Abhishek Gupta 004; Ankit Goyal 001 (CoRR, 2025)

SRSA: Skill Retrieval and Adaptation for Robotic Assembly Tasks. - Yijie Guo; Bingjie Tang; Iretiayo Akinola; Dieter Fox; Abhishek Gupta 004; Yashraj S. Narang (CoRR, 2025)

Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets. - Chuning Zhu; Raymond Yu; Siyuan Feng 003; Benjamin Burchfiel; Paarth Shah; Abhishek Gupta 004 (CoRR, 2025)

ATK: Automatic Task-driven Keypoint Selection for Robust Policy Learning. - Yunchu Zhang; Shubham Mittal 005; Zhengyu Zhang; Liyiming Ke; Siddhartha S. Srinivasa; Abhishek Gupta 004 (CoRR, 2025)

Steering Your Diffusion Policy with Latent Space Reinforcement Learning. - Andrew Wagenmaker; Mitsuhiko Nakamoto; Yunchu Zhang; Seohong Park; Waleed Yagoub; Anusha Nagabandi; Abhishek Gupta 004; Sergey Levine (CoRR, 2025)

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 S. Hu; Fabio Ramos 001; Jonathan Tremblay; Kanav Arora; et al. (CoRR, 2025)