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ORCIDPulkit Agrawal 0001
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation (PhD 2018): University of California Berkeley, CA, USA
Other persons with the same name
- Pulkit Agrawal 0002 — Apple Inc., Cupertino, CA, USA
- Pulkit Agrawal 0003 — University of California San Diego, CA, USA
- Pulkit Agrawal 0004
![[0009-0009-5786-8891]](https://dblp.org/img/orcid-mark.12x12.png "0009-0009-5786-8891")
— Games24x7, India
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2020 – today
- 2024
[j5]Changling Li, Zhang-Wei Hong, Pulkit Agrawal, Divyansh Garg, Joni Pajarinen:
ROER: Regularized Optimal Experience Replay. RLJ 4: 1598-1618 (2024)- [j4]Gabriel B. Margolis, Ge Yang, Kartik Paigwar, Tao Chen, Pulkit Agrawal:
Rapid locomotion via reinforcement learning. Int. J. Robotics Res. 43(4): 572-587 (2024) - [j3]Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R. Fiete:
Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building. Trans. Mach. Learn. Res. 2024 (2024) - [c82]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:
OpenEQA: Embodied Question Answering in the Era of Foundation Models. CVPR 2024: 16488-16498 - [c81]Andreea Bobu, Andi Peng, Pulkit Agrawal, Julie A. Shah, Anca D. Dragan:
Aligning Human and Robot Representations. HRI 2024: 42-54 - [c80]Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal:
Curiosity-driven Red-teaming for Large Language Models. ICLR 2024 - [c79]Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal:
Random Latent Exploration for Deep Reinforcement Learning. ICML 2024 - [c78]Younghyo Park, Gabriel B. Margolis, Pulkit Agrawal:
Position: Automatic Environment Shaping is the Next Frontier in RL. ICML 2024 - [c77]Meenal Parakh, Alisha Fong, Anthony Simeonov, Tao Chen, Abhishek Gupta, Pulkit Agrawal:
Lifelong Robot Learning with Human Assisted Language Planners. ICRA 2024: 523-529 - [c76]Daniel Yang, Davin Tjia, Jacob Berg, Dima Damen, Pulkit Agrawal, Abhishek Gupta:
Rank2Reward: Learning Shaped Reward Functions from Passive Video. ICRA 2024: 2806-2813 - [c75]Srinath Mahankali, Chi-Chang Lee, Gabriel B. Margolis, Zhang-Wei Hong, Pulkit Agrawal:
Maximizing Quadruped Velocity by Minimizing Energy. ICRA 2024: 11467-11473 - [c74]Tifanny Portela, Gabriel B. Margolis, Yandong Ji, Pulkit Agrawal:
Learning Force Control for Legged Manipulation. ICRA 2024: 15366-15372 - [c73]Rubén Castro Ornelas, Tomás Cantú, Isabel Sperandio, Alexander H. Slocum, Pulkit Agrawal:
Everyday finger: a robotic finger that meets the needs of everyday interactive manipulation. ICRA 2024: 16016-16023 - [c72]Branden Romero, Haoshu Fang, Pulkit Agrawal, Edward H. Adelson:
EyeSight Hand: Design of a Fully-Actuated Dexterous Robot Hand with Integrated Vision-Based Tactile Sensors and Compliant Actuation. IROS 2024: 1853-1860 - [c71]Lars Ankile, Anthony Simeonov, Idan Shenfeld, Pulkit Agrawal:
JUICER: Data-Efficient Imitation Learning for Robotic Assembly. IROS 2024: 5096-5103 - [c70]Chi-Chang Lee, Zhang-Wei Hong, Pulkit Agrawal:
Going Beyond Heuristics by Imposing Policy Improvement as a Constraint. NeurIPS 2024 - [c69]Steven Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki:
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. NeurIPS 2024 - [c68]Aviv Netanyahu, Yilun Du, Antonia Bronars, Jyothish Pari, Josh Tenenbaum, Tianmin Shu, Pulkit Agrawal:
Few-Shot Task Learning through Inverse Generative Modeling. NeurIPS 2024 - [c67]Marcel Torne Villasevil, Anthony Simeonov, Zechu Li, April Chan, Tao Chen, Abhishek Gupta, Pulkit Agrawal:
Reconciling Reality through Simulation: A Real-To-Sim-to-Real Approach for Robust Manipulation. Robotics: Science and Systems 2024 - [i90]Minyoung Huh, Brian Cheung, Jeremy Bernstein, Phillip Isola, Pulkit Agrawal:
Training Neural Networks from Scratch with Parallel Low-Rank Adapters. CoRR abs/2402.16828 (2024) - [i89]Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James R. Glass, Akash Srivastava, Pulkit Agrawal:
Curiosity-driven Red-teaming for Large Language Models. CoRR abs/2402.19464 (2024) - [i88]Marcel Torne, Anthony Simeonov, Zechu Li, April Chan, Tao Chen, Abhishek Gupta, Pulkit Agrawal:
Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation. CoRR abs/2403.03949 (2024) - [i87]Lars Ankile, Anthony Simeonov, Idan Shenfeld, Pulkit Agrawal:
JUICER: Data-Efficient Imitation Learning for Robotic Assembly. CoRR abs/2404.03729 (2024) - [i86]Daniel Yang, Davin Tjia, Jacob Berg, Dima Damen, Pulkit Agrawal, Abhishek Gupta:
Rank2Reward: Learning Shaped Reward Functions from Passive Video. CoRR abs/2404.14735 (2024) - [i85]Tifanny Portela, Gabriel B. Margolis, Yandong Ji, Pulkit Agrawal:
Learning Force Control for Legged Manipulation. CoRR abs/2405.01402 (2024) - [i84]Seungwook Han, Idan Shenfeld, Akash Srivastava, Yoon Kim, Pulkit Agrawal:
Value Augmented Sampling for Language Model Alignment and Personalization. CoRR abs/2405.06639 (2024) - [i83]Zechu Li, Rickmer Krohn, Tao Chen, Anurag Ajay, Pulkit Agrawal, Georgia Chalvatzaki:
Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. CoRR abs/2406.00681 (2024) - [i82]Changling Li, Zhang-Wei Hong, Pulkit Agrawal, Divyansh Garg, Joni Pajarinen:
ROER: Regularized Optimal Experience Replay. CoRR abs/2407.03995 (2024) - [i81]Tao Chen, Eric Cousineau, Naveen Kuppuswamy, Pulkit Agrawal:
Vegetable Peeling: A Case Study in Constrained Dexterous Manipulation. CoRR abs/2407.07884 (2024) - [i80]Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal:
Random Latent Exploration for Deep Reinforcement Learning. CoRR abs/2407.13755 (2024) - [i79]Younghyo Park, Gabriel B. Margolis, Pulkit Agrawal:
Automatic Environment Shaping is the Next Frontier in RL. CoRR abs/2407.16186 (2024) - [i78]Lars Ankile, Anthony Simeonov, Idan Shenfeld, Marcel Torne, Pulkit Agrawal:
From Imitation to Refinement - Residual RL for Precise Visual Assembly. CoRR abs/2407.16677 (2024) - [i77]Rubén Castro Ornelas, Tomás Cantú, Isabel Sperandio, Alexander H. Slocum, Pulkit Agrawal:
Everyday Finger: A Robotic Finger that Meets the Needs of Everyday Interactive Manipulation. CoRR abs/2408.04142 (2024) - [i76]Branden Romero, Haoshu Fang, Pulkit Agrawal, Edward H. Adelson:
EyeSight Hand: Design of a Fully-Actuated Dexterous Robot Hand with Integrated Vision-Based Tactile Sensors and Compliant Actuation. CoRR abs/2408.06265 (2024) - [i75]Allen Z. Ren, Justin Lidard, Lars Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz:
Diffusion Policy Policy Optimization. CoRR abs/2409.00588 (2024) - [i74]Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano, Pulkit Agrawal:
ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization. CoRR abs/2410.13837 (2024) - [i73]Jaedong Hwang, Brian Cheung, Zhang-Wei Hong, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete:
ImageNet-RIB Benchmark: Large Pre-Training Datasets Don't Guarantee Robustness after Fine-Tuning. CoRR abs/2410.21582 (2024) - [i72]Bipasha Sen, Michelle Wang, Nandini Thakur, Aditya Agarwal, Pulkit Agrawal:
Learning to Look Around: Enhancing Teleoperation and Learning with a Human-like Actuated Neck. CoRR abs/2411.00704 (2024) - [i71]Jyothish Pari, Samy Jelassi, Pulkit Agrawal:
Collective Model Intelligence Requires Compatible Specialization. CoRR abs/2411.02207 (2024) - [i70]Younghyo Park, Jagdeep Singh Bhatia, Lars Ankile, Pulkit Agrawal:
DexHub and DART: Towards Internet Scale Robot Data Collection. CoRR abs/2411.02214 (2024) - [i69]Aviv Netanyahu, Yilun Du, Antonia Bronars, Jyothish Pari, Joshua B. Tenenbaum, Tianmin Shu, Pulkit Agrawal:
Few-Shot Task Learning through Inverse Generative Modeling. CoRR abs/2411.04987 (2024) - [i68]Sathwik Karnik, Zhang-Wei Hong, Nishant Abhangi, Yen-Chen Lin, Tsun-Hsuan Wang, Pulkit Agrawal:
Embodied Red Teaming for Auditing Robotic Foundation Models. CoRR abs/2411.18676 (2024) - [i67]Marcel Torne, Arhan Jain, Jiayi Yuan, Vidaaranya Macha, Lars Ankile, Anthony Simeonov, Pulkit Agrawal, Abhishek Gupta:
Robot Learning with Super-Linear Scaling. CoRR abs/2412.01770 (2024) - [i66]Seungwook Han, Jinyeop Song, Jeff Gore, Pulkit Agrawal:
Emergence of Abstractions: Concept Encoding and Decoding Mechanism for In-Context Learning in Transformers. CoRR abs/2412.12276 (2024) - [i65]Moritz Reuss, Jyothish Pari, Pulkit Agrawal, Rudolf Lioutikov:
Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning. CoRR abs/2412.12953 (2024) - 2023
- [j2]Tao Chen, Megha Tippur, Siyang Wu, Vikash Kumar, Edward H. Adelson, Pulkit Agrawal:
Visual dexterity: In-hand reorientation of novel and complex object shapes. Sci. Robotics 8(84) (2023) - [j1]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c66]Max Balsells, Marcel Torne Villasevil, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta:
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback. CoRL 2023: 774-799 - [c65]Anthony Simeonov, Ankit Goyal, Lucas Manuelli, Yen-Chen Lin, Alina Sarmiento, Alberto Rodriguez Garcia, Pulkit Agrawal, Dieter Fox:
Shelving, Stacking, Hanging: Relational Pose Diffusion for Multi-modal Rearrangement. CoRL 2023: 2030-2069 - [c64]Gabriel B. Margolis, Xiang Fu, Yandong Ji, Pulkit Agrawal:
Learning to See Physical Properties with Active Sensing Motor Policies. CoRL 2023: 2537-2548 - [c63]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision Making? ICLR 2023 - [c62]Zhang-Wei Hong, Pulkit Agrawal, Remi Tachet des Combes, Romain Laroche:
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting. ICLR 2023 - [c61]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. ICLR 2023 - [c60]Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola:
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. ICML 2023: 14096-14113 - [c59]Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal:
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. ICML 2023: 19440-19459 - [c58]Andi Peng, Aviv Netanyahu, Mark K. Ho, Tianmin Shu, Andreea Bobu, Julie Shah, Pulkit Agrawal:
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation. ICML 2023: 27630-27641 - [c57]Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal:
TGRL: An Algorithm for Teacher Guided Reinforcement Learning. ICML 2023: 31077-31093 - [c56]Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy:
Statistical Learning under Heterogenous Distribution Shift. ICML 2023: 31800-31851 - [c55]Yandong Ji, Gabriel B. Margolis, Pulkit Agrawal:
DribbleBot: Dynamic Legged Manipulation in the Wild. ICRA 2023: 5155-5162 - [c54]Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal:
TactoFind: A Tactile Only System for Object Retrieval. ICRA 2023: 8025-8032 - [c53]Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal:
Visual Pre-Training for Navigation: What Can We Learn from Noise? IROS 2023: 3897-3902 - [c52]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. NeurIPS 2023 - [c51]Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal:
Compositional Foundation Models for Hierarchical Planning. NeurIPS 2023 - [c50]Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal:
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. NeurIPS 2023 - [c49]Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie A. Shah:
Human-Guided Complexity-Controlled Abstractions. NeurIPS 2023 - [c48]Marcel Torne Villasevil, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta:
Breadcrumbs to the Goal: Supervised Goal Selection from Human-in-the-Loop Feedback. NeurIPS 2023 - [i64]Andreea Bobu, Andi Peng, Pulkit Agrawal, Julie Shah, Anca D. Dragan:
Aligning Robot and Human Representations. CoRR abs/2302.01928 (2023) - [i63]Baxi Chong, Di Luo, Tianyu Wang, Gabriel B. Margolis, Juntao He, Pulkit Agrawal, Marin Soljacic, Daniel I. Goldman:
Geometry of contact: contact planning for multi-legged robots via spin models duality. CoRR abs/2302.03019 (2023) - [i62]Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy:
Statistical Learning under Heterogenous Distribution Shift. CoRR abs/2302.13934 (2023) - [i61]Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal:
TactoFind: A Tactile Only System for Object Retrieval. CoRR abs/2303.13482 (2023) - [i60]Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava:
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. CoRR abs/2304.00601 (2023) - [i59]Yandong Ji, Gabriel B. Margolis, Pulkit Agrawal:
DribbleBot: Dynamic Legged Manipulation in the Wild. CoRR abs/2304.01159 (2023) - [i58]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. CoRR abs/2304.14329 (2023) - [i57]Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola:
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. CoRR abs/2305.08842 (2023) - [i56]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR abs/2305.17250 (2023) - [i55]Zhang-Wei Hong, Pulkit Agrawal, Rémi Tachet des Combes, Romain Laroche:
Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting. CoRR abs/2306.13085 (2023) - [i54]Idan Shenfeld, Zhang-Wei Hong, Aviv Tamar, Pulkit Agrawal:
TGRL: An Algorithm for Teacher Guided Reinforcement Learning. CoRR abs/2307.03186 (2023) - [i53]Anthony Simeonov, Ankit Goyal, Lucas Manuelli, Yen-Chen Lin, Alina Sarmiento, Alberto Rodriguez, Pulkit Agrawal, Dieter Fox:
Shelving, Stacking, Hanging: Relational Pose Diffusion for Multi-modal Rearrangement. CoRR abs/2307.04751 (2023) - [i52]Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete:
Neuro-Inspired Efficient Map Building via Fragmentation and Recall. CoRR abs/2307.05793 (2023) - [i51]Andi Peng, Aviv Netanyahu, Mark K. Ho, Tianmin Shu, Andreea Bobu, Julie Shah, Pulkit Agrawal:
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation. CoRR abs/2307.06333 (2023) - [i50]Marcel Torne, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta:
Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback. CoRR abs/2307.11049 (2023) - [i49]Zechu Li, Tao Chen, Zhang-Wei Hong, Anurag Ajay, Pulkit Agrawal:
Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. CoRR abs/2307.12983 (2023) - [i48]Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Josh Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal:
Compositional Foundation Models for Hierarchical Planning. CoRR abs/2309.08587 (2023) - [i47]Meenal Parakh, Alisha Fong, Anthony Simeonov, Abhishek Gupta, Tao Chen, Pulkit Agrawal:
Human-Assisted Continual Robot Learning with Foundation Models. CoRR abs/2309.14321 (2023) - [i46]Zhang-Wei Hong, Aviral Kumar, Sathwik Karnik, Abhishek Bhandwaldar, Akash Srivastava, Joni Pajarinen, Romain Laroche, Abhishek Gupta, Pulkit Agrawal:
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets. CoRR abs/2310.04413 (2023) - [i45]Jaedong Hwang, Zhang-Wei Hong, Eric Chen, Akhilan Boopathy, Pulkit Agrawal, Ila Fiete:
Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity. CoRR abs/2310.17537 (2023) - [i44]Andi Peng, Mycal Tucker, Eoin M. Kenny, Noga Zaslavsky, Pulkit Agrawal, Julie Shah:
Human-Guided Complexity-Controlled Abstractions. CoRR abs/2310.17550 (2023) - [i43]Max Balsells, Marcel Torne, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta:
Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback. CoRR abs/2310.20608 (2023) - [i42]Gabriel B. Margolis, Xiang Fu, Yandong Ji, Pulkit Agrawal:
Learning to See Physical Properties with Active Sensing Motor Policies. CoRR abs/2311.01405 (2023) - 2022
- [c47]Gabriel B. Margolis, Pulkit Agrawal:
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior. CoRL 2022: 22-31 - [c46]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez Garcia, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRL 2022: 835-846 - [c45]Jie Xu, Sangwoon Kim, Tao Chen, Alberto Rodriguez Garcia, Pulkit Agrawal, Wojciech Matusik, Shinjiro Sueda:
Efficient Tactile Simulation with Differentiability for Robotic Manipulation. CoRL 2022: 1488-1498 - [c44]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations. ICLR 2022 - [c43]Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal:
Topological Experience Replay. ICLR 2022 - [c42]Zhang-Wei Hong, Ge Yang, Pulkit Agrawal:
Bi-linear Value Networks for Multi-goal Reinforcement Learning. ICLR 2022 - [c41]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming The Spectral Bias of Neural Value Approximation. ICLR 2022 - [c40]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should Be Trained to be Adaptive. ICML 2022: 7513-7530 - [c39]Aviv Netanyahu, Tianmin Shu, Joshua B. Tenenbaum, Pulkit Agrawal:
Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning. ICML 2022: 16480-16495 - [c38]Lara Zlokapa, Yiyue Luo, Jie Xu, Michael Foshey, Kui Wu, Pulkit Agrawal, Wojciech Matusik:
An Integrated Design Pipeline for Tactile Sensing Robotic Manipulators. ICRA 2022: 3136-3142 - [c37]Richard Li, Carlos Esteves, Ameesh Makadia, Pulkit Agrawal:
Stable Object Reorientation using Contact Plane Registration. ICRA 2022: 6379-6385 - [c36]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. ICRA 2022: 6394-6400 - [c35]Haokuan Luo, Albert Yue, Zhang-Wei Hong, Pulkit Agrawal:
Stubborn: A Strong Baseline for Indoor Object Navigation. IROS 2022: 3287-3293 - [c34]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS 2022 - [c33]Eric Chen, Zhang-Wei Hong, Joni Pajarinen, Pulkit Agrawal:
Redeeming intrinsic rewards via constrained optimization. NeurIPS 2022 - [c32]Gabriel B. Margolis, Ge Yang, Kartik Paigwar, Tao Chen, Pulkit Agrawal:
Rapid Locomotion via Reinforcement Learning. Robotics: Science and Systems 2022 - [i41]Haokuan Luo, Albert Yue, Zhang-Wei Hong, Pulkit Agrawal:
Stubborn: A Strong Baseline for Indoor Object Navigation. CoRR abs/2203.07359 (2022) - [i40]Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal:
Topological Experience Replay. CoRR abs/2203.15845 (2022) - [i39]Lara Zlokapa, Yiyue Luo, Jie Xu, Michael Foshey, Kui Wu, Pulkit Agrawal, Wojciech Matusik:
An Integrated Design Pipeline for Tactile Sensing Robotic Manipulators. CoRR abs/2204.07149 (2022) - [i38]Zhang-Wei Hong, Ge Yang, Pulkit Agrawal:
Bilinear value networks. CoRR abs/2204.13695 (2022) - [i37]Gabriel B. Margolis, Ge Yang, Kartik Paigwar, Tao Chen, Pulkit Agrawal:
Rapid Locomotion via Reinforcement Learning. CoRR abs/2205.02824 (2022) - [i36]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming the Spectral Bias of Neural Value Approximation. CoRR abs/2206.04672 (2022) - [i35]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should be Trained to be Adaptive. CoRR abs/2207.02200 (2022) - [i34]Richard Li, Carlos Esteves, Ameesh Makadia, Pulkit Agrawal:
Stable Object Reorientation using Contact Plane Registration. CoRR abs/2208.08962 (2022) - [i33]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - [i32]Eric Chen, Zhang-Wei Hong, Joni Pajarinen, Pulkit Agrawal:
Redeeming Intrinsic Rewards via Constrained Optimization. CoRR abs/2211.07627 (2022) - [i31]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRR abs/2211.09786 (2022) - [i30]Tao Chen, Megha Tippur, Siyang Wu, Vikash Kumar, Edward H. Adelson, Pulkit Agrawal:
Visual Dexterity: In-hand Dexterous Manipulation from Depth. CoRR abs/2211.11744 (2022) - [i29]Aviv Netanyahu, Tianmin Shu, Joshua B. Tenenbaum, Pulkit Agrawal:
Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning. CoRR abs/2211.15339 (2022) - [i28]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision-Making? CoRR abs/2211.15657 (2022) - [i27]Gabriel B. Margolis, Pulkit Agrawal:
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior. CoRR abs/2212.03238 (2022) - 2021
- [c31]Pooya Khorrami, Olga Simek, Brian Cheung, Mark Veillette, Rumen Dangovski, Ileana Rugina, Marin Soljacic, Pulkit Agrawal:
Adapting Deep Learning Models to New Meteorological Contexts Using Transfer Learning. IEEE BigData 2021: 4169-4177 - [c30]Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba:
3D Neural Scene Representations for Visuomotor Control. CoRL 2021: 112-123 - [c29]Tao Chen, Jie Xu, Pulkit Agrawal:
A System for General In-Hand Object Re-Orientation. CoRL 2021: 297-307 - [c28]Gabriel B. Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal:
Learning to Jump from Pixels. CoRL 2021: 1025-1034 - [c27]Pulkit Agrawal:
The Task Specification Problem. CoRL 2021: 1745-1751 - [c26]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR 2021 - [c25]Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola:
Learning Task Informed Abstractions. ICML 2021: 3480-3491 - [c24]Joshua Gruenstein, Tao Chen, Neel Doshi, Pulkit Agrawal:
Residual Model Learning for Microrobot Control. ICRA 2021: 7219-7226 - [c23]Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal:
An End-to-End Differentiable Framework for Contact-Aware Robot Design. Robotics: Science and Systems 2021 - [i26]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. CoRR abs/2103.10427 (2021) - [i25]Joshua Gruenstein, Tao Chen, Neel Doshi, Pulkit Agrawal:
Residual Model Learning for Microrobot Control. CoRR abs/2104.00631 (2021) - [i24]Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola:
Learning Task Informed Abstractions. CoRR abs/2106.15612 (2021) - [i23]Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba:
3D Neural Scene Representations for Visuomotor Control. CoRR abs/2107.04004 (2021) - [i22]Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal:
An End-to-End Differentiable Framework for Contact-Aware Robot Design. CoRR abs/2107.07501 (2021) - [i21]Gabriel B. Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal:
Learning to Jump from Pixels. CoRR abs/2110.15344 (2021) - [i20]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Contrastive Learning. CoRR abs/2111.00899 (2021) - [i19]Tao Chen, Jie Xu, Pulkit Agrawal:
A System for General In-Hand Object Re-Orientation. CoRR abs/2111.03043 (2021) - [i18]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. CoRR abs/2112.05124 (2021) - 2020
- [c22]Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik:
Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci 2020 - [c21]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRL 2020: 1582-1601 - [c20]Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal:
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning. ICRA 2020: 4051-4058 - [i17]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR abs/2010.13611 (2020) - [i16]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRR abs/2011.08177 (2020)
2010 – 2019
- 2019
- [c19]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Tom Griffiths:
Human-level but not human-like: Deep Reinforcement Learning in the dark. CogSci 2019: 3265 - [c18]Eliza Kosoy, Deepak Pathak, Pulkit Agrawal, Alison Gopnik:
Curiouser and Curiouser: Children's intrinsic exploration of mazes and its effects on reaching a goal. CogSci 2019: 3496 - [c17]Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen:
Superposition of many models into one. NeurIPS 2019: 10867-10876 - [i15]Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen:
Superposition of many models into one. CoRR abs/1902.05522 (2019) - [i14]Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal:
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning. CoRR abs/1912.11032 (2019) - 2018
- [b1]Pulkit Agrawal:
Computational Sensorimotor Learning. University of California, Berkeley, USA, 2018 - [c16]Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik:
Learning Instance Segmentation by Interaction. CVPR Workshops 2018: 2042-2045 - [c15]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. CVPR Workshops 2018: 2050-2053 - [c14]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Thomas L. Griffiths:
Investigating Human Priors for Playing Video Games. ICLR (Workshop) 2018 - [c13]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. ICLR 2018 - [c12]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Tom Griffiths, Alexei A. Efros:
Investigating Human Priors for Playing Video Games. ICML 2018: 1348-1356 - [i13]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Thomas L. Griffiths, Alexei A. Efros:
Investigating Human Priors for Playing Video Games. CoRR abs/1802.10217 (2018) - [i12]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. CoRR abs/1804.08606 (2018) - [i11]Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik:
Learning Instance Segmentation by Interaction. CoRR abs/1806.08354 (2018) - 2017
- [c11]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-Driven Exploration by Self-Supervised Prediction. CVPR Workshops 2017: 488-489 - [c10]Panna Felsen, Pulkit Agrawal, Jitendra Malik:
What will Happen Next? Forecasting Player Moves in Sports Videos. ICCV 2017: 3362-3371 - [c9]Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas:
Learning to Perform Physics Experiments via Deep Reinforcement Learning. ICLR (Poster) 2017 - [c8]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-driven Exploration by Self-supervised Prediction. ICML 2017: 2778-2787 - [c7]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining self-supervised learning and imitation for vision-based rope manipulation. ICRA 2017: 2146-2153 - [i10]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation. CoRR abs/1703.02018 (2017) - [i9]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-driven Exploration by Self-supervised Prediction. CoRR abs/1705.05363 (2017) - [i8]Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese:
Generic 3D Representation via Pose Estimation and Matching. CoRR abs/1710.08247 (2017) - 2016
- [c6]João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, Jitendra Malik:
Human Pose Estimation with Iterative Error Feedback. CVPR 2016: 4733-4742 - [c5]Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese:
Generic 3D Representation via Pose Estimation and Matching. ECCV (3) 2016: 535-553 - [c4]Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik:
Learning Visual Predictive Models of Physics for Playing Billiards. ICLR (Poster) 2016 - [i7]Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Learning to Poke by Poking: Experiential Learning of Intuitive Physics. CoRR abs/1606.07419 (2016) - [i6]Mi-Young Huh, Pulkit Agrawal, Alexei A. Efros:
What makes ImageNet good for transfer learning? CoRR abs/1608.08614 (2016) - [i5]Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas:
Learning to Perform Physics Experiments via Deep Reinforcement Learning. CoRR abs/1611.01843 (2016) - 2015
- [c3]Pulkit Agrawal, João Carreira, Jitendra Malik:
Learning to See by Moving. ICCV 2015: 37-45 - [i4]Pulkit Agrawal, João Carreira, Jitendra Malik:
Learning to See by Moving. CoRR abs/1505.01596 (2015) - [i3]João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, Jitendra Malik:
Human Pose Estimation with Iterative Error Feedback. CoRR abs/1507.06550 (2015) - 2014
- [c2]Pulkit Agrawal, Ross B. Girshick, Jitendra Malik:
Analyzing the Performance of Multilayer Neural Networks for Object Recognition. ECCV (7) 2014: 329-344 - [i2]Pulkit Agrawal, Ross B. Girshick, Jitendra Malik:
Analyzing the Performance of Multilayer Neural Networks for Object Recognition. CoRR abs/1407.1610 (2014) - [i1]Pulkit Agrawal, Dustin Stansbury, Jitendra Malik, Jack L. Gallant:
Pixels to Voxels: Modeling Visual Representation in the Human Brain. CoRR abs/1407.5104 (2014) - 2011
- [c1]Gahgene Gweon, Pulkit Agrawal, Mikesh Udani, Bhiksha Raj, Carolyn P. Rosé:
The automatic assessment of knowledge integration processes in project teams. CSCL 2011
Coauthor Index
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