Zhu, Yuke

What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Mandlekar, A., Xu, D., Wong, J., Nasiriany, S., Wang, C., Kulkarni, R., Fei-Fei, L., Savarese, S., Zhu, Y., & Martín-Martín, R. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 66

Bottom-Up Skill Discovery From Unsegmented Demonstrations for Long-Horizon Robot Manipulation

Zhu, Y., Stone, P., & Zhu, Y. (2022) · IEEE Robotics and Automation Letters

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 50

Learning Multi-Arm Manipulation Through Collaborative Teleoperation

Tung, A., Wong, J., Mandlekar, A., Martín-Martín, R., Zhu, Y., Fei-Fei, L., & Savarese, S. (2020) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 49

Scaling Robot Supervision to Hundreds of Hours with RoboTurk: Robotic Manipulation Dataset through Human Reasoning and Dexterity

Mandlekar, A., Booher, J., Spero, M., Tung, A., Gupta, A., Zhu, Y., Garg, A., Savarese, S., & Fei-Fei, L. (2019) · arXiv

Robot Manipulation and LearningTeleoperation and Haptic Systems

Cited by 48

MimicPlay: Long-horizon imitation learning by watching human play

Wang, C., Fan, L., Sun, J., Zhang, R., Fei-Fei, L., Xu, D., Zhu, Y., & Anandkumar, A. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 43

Human-in-the-Loop Imitation Learning using Remote Teleoperation

Mandlekar, A., Xu, D., Martín-Martín, R., Zhu, Y., Fei-Fei, L., & Savarese, S. (2020) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 35

Detect, Reject, Correct: Crossmodal Compensation of Corrupted Sensors

Lee, M. A., Tan, M., Zhu, Y., & Bohg, J. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 24

DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning

Jiang, Z., Xie, Y., Lin, K., Xu, Z., Wan, W., Mandlekar, A., Fan, L. J., & Zhu, Y. (2025) · 2025 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 24

Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception

Hsu, C.-C., Jiang, Z., & Zhu, Y. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 21

ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems

Harrison, J., Garg, A., Ivanovic, B., Zhu, Y., Savarese, S., Fei-Fei, L., & Pavone, M. (2017) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 21

Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception

Hsu, C.-C., Jiang, Z., & Zhu, Y. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 21

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs

Nasiriany, S., Xia, F., Yu, W., Xiao, T., Liang, J., Dasgupta, I., Xie, A., Driess, D., Wahid, A., Xu, Z., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 13

Learning and Retrieval from Prior Data for Skill-based Imitation Learning

Nasiriany, S., Gao, T., Mandlekar, A., & Zhu, Y. (2022) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 13

LEGATO: Cross-Embodiment Imitation Using a Grasping Tool

Seo, M., Park, H. A., Yuan, S., Zhu, Y., & Sentis, L. (2025) · IEEE Robotics and Automation Letters

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 11

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

NVIDIA, :, Bjorck, J., Castañeda, F., Cherniadev, N., Da, X., Ding, R., Fan, L. "., Fang, Y., Fox, D., et al. (2025) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 10

Okami: Teaching humanoid robots manipulation skills through single video imitation

Li, J., Zhu, Y., Xie, Y., Jiang, Z., Seo, M., Pavlakos, G., & Zhu, Y. (2024) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 3

Learning Generalizable Manipulation Policies with Object-Centric 3D Representations

Zhu, Y., Jiang, Z., Stone, P., & Zhu, Y. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 2

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Chen, Y., Xue, F., Li, D., Hu, Q., Zhu, L., Li, X., Fang, Y., Tang, H., Yang, S., Liu, Z., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 2

World Simulation with Video Foundation Models for Physical AI

NVIDIA, :, Ali, A., Bai, J., Bala, M., Balaji, Y., Blakeman, A., Cai, T., Cao, J., Cao, T., et al. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1

EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data

Zheng, R., Niu, D., Xie, Y., Wang, J., Xu, M., Jiang, Y., Castañeda, F., Hu, F., Tan, Y. L., Fu, L., et al. (2026) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 0

Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning

Luo, Z., Tessler, C., Lin, T., Yuan, Y., He, T., Xiao, W., Guo, Y., Chechik, G., Kitani, K., Fan, L., et al. (2025) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 0