Rajeswaran, Aravind

44 publications

ICML 2025 From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs Ang Cao, Sergio Arnaud, Oleksandr Maksymets, Jianing Yang, Ayush Jain, Ada Martin, Vincent-Pierre Berges, Paul Mcvay, Ruslan Partsey, Aravind Rajeswaran, Franziska Meier, Justin Johnson, Jeong Joon Park, Alexander Sax

ICML 2025 LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D Paul Mcvay, Sergio Arnaud, Ada Martin, Arjun Majumdar, Krishna Murthy Jatavallabhula, Phillip Thomas, Ruslan Partsey, Daniel Dugas, Abha Gejji, Alexander Sax, Vincent-Pierre Berges, Mikael Henaff, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

CVPR 2024 OpenEQA: Embodied Question Answering in the Era of Foundation Models Arjun Majumdar, Anurag Ajay, Xiaohan Zhang, Pranav Putta, Sriram Yenamandra, Mikael Henaff, Sneha Silwal, Paul Mcvay, Oleksandr Maksymets, Sergio Arnaud, Karmesh Yadav, Qiyang Li, Ben Newman, Mohit Sharma, Vincent Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan, Franziska Meier, Chris Paxton, Alexander Sax, Aravind Rajeswaran

ICML 2023 Masked Trajectory Models for Prediction, Representation, and Control Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

ICLRW 2023 Masked Trajectory Models for Prediction, Representation, and Control Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran

ICLR 2023 MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran

ICML 2023 On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline Nicklas Hansen, Zhecheng Yuan, Yanjie Ze, Tongzhou Mu, Aravind Rajeswaran, Hao Su, Huazhe Xu, Xiaolong Wang

NeurIPS 2023 RoboHive: A Unified Framework for Robot Learning Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran

NeurIPS 2023 Where Are We in the Search for an Artificial Visual Cortex for Embodied Intelligence? Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

ICLRW 2023 Where Are We in the Search for an Artificial Visual Cortex for Embodied Intelligence? Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

L4DC 2022 Can Foundation Models Perform Zero-Shot Task Specification for Robot Manipulation? Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran

NeurIPSW 2022 MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran

ICMLW 2022 Policy Architectures for Compositional Generalization in Control Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran

NeurIPSW 2022 Policy Architectures for Compositional Generalization in Control Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran

CoRL 2022 R3M: A Universal Visual Representation for Robot Manipulation Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Real World Offline Reinforcement Learning with Realistic Data Source Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar

NeurIPSW 2022 Real World Offline Reinforcement Learning with Realistic Data Source Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar

ICML 2022 The Unsurprising Effectiveness of Pre-Trained Vision Models for Control Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

NeurIPSW 2022 Train Offline, Test Online: A Real Robot Learning Benchmark Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta

ICML 2022 Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots Tanmay Shankar, Yixin Lin, Aravind Rajeswaran, Vikash Kumar, Stuart Anderson, Jean Oh

NeurIPS 2022 Unsupervised Reinforcement Learning with Contrastive Intrinsic Control Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

NeurIPSW 2021 Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin

NeurIPSW 2021 CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

NeurIPS 2021 COMBO: Conservative Offline Model-Based Policy Optimization Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn

NeurIPS 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

ICMLW 2021 Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch

L4DC 2021 Offline Reinforcement Learning from Images with Latent Space Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

NeurIPS 2021 Reinforcement Learning with Latent Flow Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Misha Laskin

NeurIPS 2021 Visual Adversarial Imitation Learning Using Variational Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

ICMLW 2021 Visual Adversarial Imitation Learning Using Variational Models Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn

ICML 2020 A Game Theoretic Framework for Model Based Reinforcement Learning Aravind Rajeswaran, Igor Mordatch, Vikash Kumar

L4DC 2020 Lyceum: An Efficient and Scalable Ecosystem for Robot Learning Colin Summers, Kendall Lowrey, Aravind Rajeswaran, Siddhartha Srinivasa, Emanuel Todorov

NeurIPS 2020 MOReL: Model-Based Offline Reinforcement Learning Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims

NeurIPS 2019 Meta-Learning with Implicit Gradients Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine

ICML 2019 Online Meta-Learning Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine

ICLRW 2019 Online Meta-Learning Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine

ICLR 2019 Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, Igor Mordatch

ICLR 2018 Divide-and-Conquer Reinforcement Learning Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine

ICLR 2018 Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M Bayen, Sham Kakade, Igor Mordatch, Pieter Abbeel

ICLR 2017 EPOpt: Learning Robust Neural Network Policies Using Model Ensembles Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine

NeurIPS 2017 Towards Generalization and Simplicity in Continuous Control Aravind Rajeswaran, Kendall Lowrey, Emanuel V. Todorov, Sham M. Kakade