Edward S. Hu

According to our database, Edward S. Hu authored at least 19 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

TiPToP: A Modular Open-Vocabulary Planning System for Robotic Manipulation.

William Shen, Nishanth Kumar, Sahit Chintalapudi, Jie Wang, Christopher Watson, Edward S. Hu, Jing Cao, Dinesh Jayaraman, Leslie Pack Kaelbling, Tomás Lozano-Pérez

CoRR, March, 2026

2025

Next-Latent Prediction Transformers Learn Compact World Models.

Jayden Teoh, Manan Tomar, Kwangjun Ahn, Edward S. Hu, Pratyusha Sharma, Riashat Islam, Alex Lamb, John Langford

CoRR, November, 2025

Guiding Skill Discovery with Foundation Models.

Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat, Vincent François-Lavet, Edward S. Hu

CoRR, October, 2025

RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies.

Pranav Atreya, Karl Pertsch, Tony Lee, Moo Jin Kim, Arhan Jain, Artur Kuramshin, Clemens Eppner, Cyrus Neary, Edward S. Hu, Fabio Ramos, Jonathan Tremblay, Kanav Arora, Kirsty Ellis, Luca Macesanu, Matthew Leonard, Meedeum Cho, Ozgur Aslan, Shivin Dass, Jie Wang, Xingfang Yuan, Xuning Yang, Abhishek Gupta, Dinesh Jayaraman, Glen Berseth, Kostas Daniilidis, Roberto Martin Martin, Youngwoon Lee, Percy Liang, Chelsea Finn, Sergey Levine

CoRR, June, 2025

Reset-free Reinforcement Learning with World Models.

Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat, Edward S. Hu

Trans. Mach. Learn. Res., 2025

Real-World Reinforcement Learning of Active Perception Behaviors.

Edward S. Hu, Jie Wang, Xingfang Yuan, Fiona Luo, Muyao Li, Gaspard Lambrechts, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

The Value of Sensory Information to a Robot.

Arjun Krishna, Edward S. Hu, Dinesh Jayaraman

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

The Belief State Transformer.

Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Learning to Achieve Goals with Belief State Transformers.

Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford

CoRR, 2024

World Models Increase Autonomy in Reinforcement Learning.

Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat, Edward S. Hu

CoRR, 2024

Privileged Sensing Scaffolds Reinforcement Learning.

Edward S. Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Planning Goals for Exploration.

Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Know Thyself: Transferable Visual Control Policies Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Tenth International Conference on Learning Representations, 2022

Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning.

Kun Huang, Edward S. Hu, Dinesh Jayaraman

Proceedings of the Conference on Robot Learning, 2022

2021

Know Thyself: Transferable Visuomotor Control Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

CoRR, 2021

IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks.

Youngwoon Lee, Edward S. Hu, Joseph J. Lim

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2019

IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks.

Youngwoon Lee, Edward S. Hu, Zhengyu Yang, Alex Yin, Joseph J. Lim

CoRR, 2019

Composing Complex Skills by Learning Transition Policies.

Youngwoon Lee, Shao-Hua Sun, Sriram Somasundaram, Edward S. Hu, Joseph J. Lim

Proceedings of the 7th International Conference on Learning Representations, 2019

To Follow or not to Follow: Selective Imitation Learning from Observations.

Youngwoon Lee, Edward S. Hu, Zhengyu Yang, Joseph J. Lim

Proceedings of the 3rd Annual Conference on Robot Learning, 2019