Abbeel, Pieter

DoorGym: A Scalable Door Opening Environment And Baseline Agent

Urakami, Y., Hodgkinson, A., Carlin, C., Leu, R., Rigazio, L., & Abbeel, P. (2019) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 30

Chain of Hindsight Aligns Language Models with Feedback

Liu, H., Sferrazza, C., & Abbeel, P. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 30

Learning Visual Robotic Control Efficiently with Contrastive Pre-training and Data Augmentation

Zhan, A., Zhao, R., Pinto, L., Abbeel, P., & Laskin, M. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 28

Ring Attention with Blockwise Transformers for Near-Infinite Context

Liu, H., Zaharia, M., & Abbeel, P. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 23

Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning

Seo, Y., Lee, K., Clavera, I., Kurutach, T., Shin, J., & Abbeel, P. (2020) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 20

World Model on Million-Length Video And Language With Blockwise RingAttention

Liu, H., Yan, W., Zaharia, M., & Abbeel, P. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 14

The Wisdom of Hindsight Makes Language Models Better Instruction Followers

Zhang, T., Liu, F., Wong, J., Abbeel, P., & Gonzalez, J. E. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 13

A non-rigid point and normal registration algorithm with applications to learning from demonstrations

Lee, A. X., Goldstein, M. A., Barratt, S. T., & Abbeel, P. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 12

MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting

Liu, F., Fang, K., Abbeel, P., & Levine, S. (2024) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 8

Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game

Toyer, S., Watkins, O., Mendes, E. A., Svegliato, J., Bailey, L., Wang, T., Ong, I., Elmaaroufi, K., Abbeel, P., Darrell, T., et al. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 7

Dichotomy of Control: Separating What You Can Control from What You Cannot

Yang, M., Schuurmans, D., Abbeel, P., & Nachum, O. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 6

One Step Diffusion via Shortcut Models

Frans, K., Hafner, D., Levine, S., & Abbeel, P. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 3

ElasticTok: Adaptive Tokenization for Image and Video

Yan, W., Mnih, V., Faust, A., Zaharia, M., Abbeel, P., & Liu, H. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 1

OSGym: Scalable OS Infra for Computer Use Agents

Qin, Z., Chen, J., Man, Y., Cao, S., Pang, Z., Wang, Z., Fang, H., Zhu, L., Xie, Z., Wei, Z., et al. (2025) · arXiv

Cloud Computing and Resource ManagementCloud Computing and Remote Desktop Technologies

Cited by 0

Efficient Long Video Tokenization via Coordinate-based Patch Reconstruction

Jang, H., Yu, S., Shin, J., Abbeel, P., & Seo, Y. (2024) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 0