Aravind Rajeswaran
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
22
Venues
6
Active years
2017–2025
Best venue rank
A*
Where they publish
Papers
22 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICML | 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 |
| 2025 | ICML | 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 |
| 2024 | CVPR | 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-Pierre Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan, Franziska Meier, Chris Paxton, Alexander Sax, Aravind Rajeswaran |
| 2024 | ICRA | MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation. | Patrick Lancaster, Nicklas Hansen, Aravind Rajeswaran, Vikash Kumar |
| 2024 | IROS | From LLMs to Actions: Latent Codes as Bridges in Hierarchical Robot Control. | Yide Shentu, Philipp Wu, Aravind Rajeswaran, Pieter Abbeel |
| 2024 | ICRA | What Do We Learn from a Large-Scale Study of Pre-Trained Visual Representations in Sim and Real Environments? | 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 | ICLR | MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations. | Nicklas Hansen, Yixin Lin, Hao Su, Xiaolong Wang, Vikash Kumar, Aravind Rajeswaran |
| 2023 | ICML | 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 |
| 2023 | ICML | Masked Trajectory Models for Prediction, Representation, and Control. | Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran |
| 2023 | ICRA | Train Offline, Test Online: A Real Robot Learning Benchmark. | 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 | ICRA | Real World Offline Reinforcement Learning with Realistic Data Source. | Gaoyue Zhou, Liyiming Ke, Siddhartha S. Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar |
| 2022 | CoRL | R3M: A Universal Visual Representation for Robot Manipulation. | Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, Abhinav Gupta |
| 2022 | ICML | The Unsurprising Effectiveness of Pre-Trained Vision Models for Control. | Simone Parisi, Aravind Rajeswaran, Senthil Purushwalkam, Abhinav Gupta |
| 2022 | ICML | Translating Robot Skills: Learning Unsupervised Skill Correspondences Across Robots. | Tanmay Shankar, Yixin Lin, Aravind Rajeswaran, Vikash Kumar, Stuart Anderson, Jean Oh |
| 2020 | ICML | A Game Theoretic Framework for Model Based Reinforcement Learning. | Aravind Rajeswaran, Igor Mordatch, Vikash Kumar |
| 2019 | ICLR | Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. | Kendall Lowrey, Aravind Rajeswaran, Sham M. Kakade, Emanuel Todorov, Igor Mordatch |
| 2019 | ICML | Online Meta-Learning. | Chelsea Finn, Aravind Rajeswaran, Sham M. Kakade, Sergey Levine |
| 2019 | ICRA | Learning Deep Visuomotor Policies for Dexterous Hand Manipulation. | Divye Jain, Andrew Li, Shivam Singhal, Aravind Rajeswaran, Vikash Kumar, Emanuel Todorov |
| 2019 | ICRA | Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost. | Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine, Vikash Kumar |
| 2018 | ICLR | Divide-and-Conquer Reinforcement Learning. | Dibya Ghosh, Avi Singh, Aravind Rajeswaran, Vikash Kumar, Sergey Levine |
| 2018 | ICLR | Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. | Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, Pieter Abbeel |
| 2017 | ICLR | EPOpt: Learning Robust Neural Network Policies Using Model Ensembles. | Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran, Sergey Levine |