Aravind Rajeswaran

85 papers A* 25A 1C 1Misc 1Journal 46Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fara-7B: An Efficient Agentic Model for Computer Use. CoRR Ahmed Awadallah, Yash Lara, Raghav Magazine, Hussein Mozannar, Akshay Nambi, Yash Pandya, Aravind Rajeswaran, Corby Rosset, Alexey Taymanov, Vibhav Vineet, Spencer Whitehead, Andrew Zhao
2025	A*	`conf`	From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs. ICML 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
2025	J	`jnl`	LIFT-GS: Cross-Scene Render-Supervised Distillation for 3D Language Grounding. CoRR Ang Cao, Sergio Arnaud, Oleksandr Maksymets, Jianing Yang, Ayush Jain, Sriram Yenamandra, Ada Martin, Vincent-Pierre Berges, Paul McVay, Ruslan Partsey, Aravind Rajeswaran, Franziska Meier, Justin Johnson, Jeong Joon Park, Alexander Sax
2025	A*	`conf`	LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D. ICML 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
2025	J	`jnl`	Locate 3D: Real-World Object Localization via Self-Supervised Learning in 3D. CoRR Sergio Arnaud, Paul McVay, 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
2024	A	`conf`	From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control. IROS Yide Shentu, Philipp Wu, Aravind Rajeswaran, Pieter Abbeel
2024	J	`jnl`	From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control. CoRR Yide Shentu, Philipp Wu, Aravind Rajeswaran, Pieter Abbeel
2024	A*	`conf`	MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation. ICRA Patrick Lancaster, Nicklas Hansen, Aravind Rajeswaran, Vikash Kumar
2024	A*	`conf`	OpenEQA: Embodied Question Answering in the Era of Foundation Models. CVPR 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-Pierre Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan, Franziska Meier, Chris Paxton, Alexander Sax, Aravind Rajeswaran
2024	J	`jnl`	Policy Architectures for Compositional Generalization in Control. RLJ Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran
2024	J	`jnl`	Semi-Supervised One Shot Imitation Learning. RLJ Philipp Wu, Kourosh Hakhamaneshi, Yuqing Du, Igor Mordatch, Aravind Rajeswaran, Pieter Abbeel
2024	J	`jnl`	Semi-Supervised One-Shot Imitation Learning. CoRR Philipp Wu, Kourosh Hakhamaneshi, Yuqing Du, Igor Mordatch, Aravind Rajeswaran, Pieter Abbeel
2024	A*	`conf`	What Do We Learn from a Large-Scale Study of Pre-Trained Visual Representations in Sim and Real Environments? ICRA Sneha Silwal, Karmesh Yadav, Tingfan Wu, Jay Vakil, Arjun Majumdar, Sergio Arnaud, Claire Chen, Vincent-Pierre Berges, Dhruv Batra, Aravind Rajeswaran, Mrinal Kalakrishnan, Franziska Meier, Oleksandr Maksymets
2023	A*	`conf`	Masked Trajectory Models for Prediction, Representation, and Control. ICML Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran
2023	J	`jnl`	Masked Trajectory Models for Prediction, Representation, and Control. CoRR Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran
2023	J	`jnl`	MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation. CoRR Patrick Lancaster, Nicklas Hansen, Aravind Rajeswaran, Vikash Kumar
2023	A*	`conf`	MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations. ICLR Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran
2023	A*	`conf`	On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline. ICML Nicklas Hansen, Zhecheng Yuan, Yanjie Ze, Tongzhou Mu, Aravind Rajeswaran, Hao Su, Huazhe Xu, Xiaolong Wang
2023	A*	`conf`	Real World Offline Reinforcement Learning with Realistic Data Source. ICRA Gaoyue Zhou, Liyiming Ke, Siddhartha S. Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar
2023	A*	`conf`	RoboHive: A Unified Framework for Robot Learning. NeurIPS Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Abhishek Gupta, Aravind Rajeswaran
2023	J	`jnl`	RoboHive: A Unified Framework for Robot Learning. CoRR Vikash Kumar, Rutav M. Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Jay Vakil, Abhishek Gupta, Aravind Rajeswaran
2023	A*	`conf`	Train Offline, Test Online: A Real Robot Learning Benchmark. ICRA Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
2023	J	`jnl`	Train Offline, Test Online: A Real Robot Learning Benchmark. CoRR Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, Abhinav Gupta
2023	J	`jnl`	What do we learn from a large-scale study of pre-trained visual representations in sim and real environments? CoRR Sneha Silwal, Karmesh Yadav, Tingfan Wu, Jay Vakil, Arjun Majumdar, Sergio Arnaud, Claire Chen, Vincent-Pierre Berges, Dhruv Batra, Aravind Rajeswaran, Mrinal Kalakrishnan, Franziska Meier, Oleksandr Maksymets
2023	A*	`conf`	Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? NeurIPS Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng 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
2023	J	`jnl`	Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? CoRR Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier
2022	J	`jnl`	CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning. CoRR Zhao Mandi, Homanga Bharadhwaj, Vincent Moens, Shuran Song, Aravind Rajeswaran, Vikash Kumar
2022	J	`jnl`	CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery. CoRR Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
2022	—	`conf`	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? L4DC Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
2022	J	`jnl`	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? CoRR Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
2022	J	`jnl`	MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations. CoRR Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran
2022	J	`jnl`	On Pre-Training for Visuo-Motor Control: Revisiting a Learning-from-Scratch Baseline. CoRR Nicklas Hansen, Zhecheng Yuan, Yanjie Ze, Tongzhou Mu, Aravind Rajeswaran, Hao Su, Huazhe Xu, Xiaolong Wang
2022	J	`jnl`	Policy Architectures for Compositional Generalization in Control. CoRR Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran
2022	Misc	`conf`	R3M: A Universal Visual Representation for Robot Manipulation. CoRL Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta
2022	J	`jnl`	R3M: A Universal Visual Representation for Robot Manipulation. CoRR Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta
2022	J	`jnl`	Real World Offline Reinforcement Learning with Realistic Data Source. CoRR Gaoyue Zhou, Liyiming Ke, Siddhartha S. Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar
2022	A*	`conf`	The Unsurprising Effectiveness of Pre-Trained Vision Models for Control. ICML Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, Abhinav Gupta
2022	J	`jnl`	The Unsurprising Effectiveness of Pre-Trained Vision Models for Control. CoRR Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, Abhinav Gupta
2022	A*	`conf`	Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots. ICML Tanmay Shankar, Yixin Lin, Aravind Rajeswaran, Vikash Kumar, Stuart Anderson, Jean Oh
2022	A*	`conf`	Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. NeurIPS Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
2021	J	`jnl`	Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL. CoRR Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin
2021	—	`—`	Broad Generalization through Domain Transfer: Abstractions and Algorithms. Aravind Rajeswaran
2021	A*	`conf`	COMBO: Conservative Offline Model-Based Policy Optimization. NeurIPS Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021	J	`jnl`	COMBO: Conservative Offline Model-Based Policy Optimization. CoRR Tianhe Yu, Aviral Kumar, Rafael Rafailov, Aravind Rajeswaran, Sergey Levine, Chelsea Finn
2021	A*	`conf`	Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	J	`jnl`	Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	—	`conf`	Offline Reinforcement Learning from Images with Latent Space Models. L4DC Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2021	A*	`conf`	Reinforcement Learning with Latent Flow. NeurIPS Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
2021	J	`jnl`	Reinforcement Learning with Latent Flow. CoRR Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
2021	A*	`conf`	Visual Adversarial Imitation Learning using Variational Models. NeurIPS Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2021	J	`jnl`	Visual Adversarial Imitation Learning using Variational Models. CoRR Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2020	A*	`conf`	A Game Theoretic Framework for Model Based Reinforcement Learning. ICML Aravind Rajeswaran, Igor Mordatch, Vikash Kumar
2020	J	`jnl`	A Game Theoretic Framework for Model Based Reinforcement Learning. CoRR Aravind Rajeswaran, Igor Mordatch, Vikash Kumar
2020	—	`conf`	Lyceum: An efficient and scalable ecosystem for robot learning. L4DC Colin Summers, Kendall Lowrey, Aravind Rajeswaran, Siddhartha S. Srinivasa, Emanuel Todorov
2020	J	`jnl`	Lyceum: An efficient and scalable ecosystem for robot learning. CoRR Colin Summers, Kendall Lowrey, Aravind Rajeswaran, Siddhartha S. Srinivasa, Emanuel Todorov
2020	J	`jnl`	MOReL : Model-Based Offline Reinforcement Learning. CoRR Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims
2020	A*	`conf`	MOReL: Model-Based Offline Reinforcement Learning. NeurIPS Rahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims
2020	J	`jnl`	Offline Reinforcement Learning from Images with Latent Space Models. CoRR Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, Chelsea Finn
2019	A*	`conf`	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. ICRA Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar
2019	A*	`conf`	Learning Deep Visuomotor Policies for Dexterous Hand Manipulation. ICRA Divye Jain, Andrew Li, Shivam Singhal, Aravind Rajeswaran, Vikash Kumar, Emanuel Todorov
2019	A*	`conf`	Meta-Learning with Implicit Gradients. NeurIPS Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	Meta-Learning with Implicit Gradients. CoRR Aravind Rajeswaran, Chelsea Finn, Sham M. Kakade, Sergey Levine
2019	A*	`conf`	Online Meta-Learning. ICML Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine
2019	J	`jnl`	Online Meta-Learning. CoRR Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine
2019	—	`conf`	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. ICLR (Poster) Kendall Lowrey, Aravind Rajeswaran, Sham M. Kakade, Emanuel Todorov, Igor Mordatch
2018	J	`jnl`	A graph partitioning algorithm for leak detection in water distribution networks. Comput. Chem. Eng. Aravind Rajeswaran, Sridharakumar Narasimhan, Shankar Narasimhan
2018	J	`jnl`	Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. CoRR Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar
2018	—	`conf`	Divide-and-Conquer Reinforcement Learning. ICLR (Poster) Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2018	J	`jnl`	Identifying Topology of Low Voltage Distribution Networks Based on Smart Meter Data. IEEE Trans. Smart Grid Satya Jayadev P., Nirav Pravinbhai Bhatt, Ramkrishna Pasumarthy, Aravind Rajeswaran
2018	—	`conf`	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. Robotics: Science and Systems Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov, Sergey Levine
2018	J	`jnl`	Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. CoRR Kendall Lowrey, Aravind Rajeswaran, Sham M. Kakade, Emanuel Todorov, Igor Mordatch
2018	—	`conf`	Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system. SIMPAR Kendall Lowrey, Svetoslav Kolev, Jeremy Dao, Aravind Rajeswaran, Emanuel Todorov
2018	J	`jnl`	Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system. CoRR Kendall Lowrey, Svetoslav Kolev, Jeremy Dao, Aravind Rajeswaran, Emanuel Todorov
2018	—	`conf`	Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. ICLR Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, Pieter Abbeel
2018	J	`jnl`	Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. CoRR Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, Pieter Abbeel
2017	J	`jnl`	Divide-and-Conquer Reinforcement Learning. CoRR Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine
2017	—	`conf`	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. ICLR (Poster) Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine
2017	J	`jnl`	Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations. CoRR Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine
2017	—	`conf`	Towards Generalization and Simplicity in Continuous Control. NIPS Aravind Rajeswaran, Kendall Lowrey, Emanuel Todorov, Sham M. Kakade
2017	J	`jnl`	Towards Generalization and Simplicity in Continuous Control. CoRR Aravind Rajeswaran, Kendall Lowrey, Emanuel Todorov, Sham M. Kakade
2016	J	`jnl`	A Graph Partitioning Algorithm for Leak Detection in Water Distribution Networks. CoRR Aravind Rajeswaran, Sridharakumar Narasimhan, Shankar Narasimhan
2016	C	`conf`	A novel approach for phase identification in smart grids using Graph Theory and Principal Component Analysis. ACC Satya Jayadev P., Aravind Rajeswaran, Nirav Pravinbhai Bhatt, Ramkrishna Pasumarthy
2016	J	`jnl`	EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. CoRR Aravind Rajeswaran, Sarvjeet Ghotra, Sergey Levine, Balaraman Ravindran
2016	J	`jnl`	Identifying Topology of Power Distribution Networks Based on Smart Meter Data. CoRR Satya Jayadev P., Nirav Pravinbhai Bhatt, Ramkrishna Pasumarthy, Aravind Rajeswaran
2015	J	`jnl`	A New Method for Reconstructing Network Topology from Flux Measurements. CoRR Aravind Rajeswaran, Shankar Narasimhan