Yu, Tianhe

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Gradient Surgery for Multi-Task Learning

Yu, T., Kumar, S., Gupta, A., Levine, S., Hausman, K., & Finn, C. (2020) · arXiv

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 755

RT-1: Robotics Transformer for Real-World Control at Scale

Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Dabis, J., Finn, C., Gopalakrishnan, K., Hausman, K., Herzog, A., Hsu, J., et al. (2022) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 727

PaLM-E: An Embodied Multimodal Language Model

Driess, D., Xia, F., Sajjadi, M. S. M., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 591

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

Yu, T., Quillen, D., He, Z., Julian, R., Narayan, A., Shively, H., Bellathur, A., Hausman, K., Finn, C., & Levine, S. (2019) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 450

One-Shot Visual Imitation Learning via Meta-Learning

Finn, C., Yu, T., Zhang, T., Abbeel, P., & Levine, S. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 341

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Brohan, A., Brown, N., Carbajal, J., Chebotar, Y., Chen, X., Choromanski, K., Ding, T., Driess, D., Dubey, A., Finn, C., et al. (2023) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 276

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0

O’Neill, A., Rehman, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., Mandlekar, A., Jain, A., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 210

Efficiently Identifying Task Groupings for Multi-Task Learning

Fifty, C., Amid, E., Zhao, Z., Yu, T., Anil, R., & Finn, C. (2021) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 125

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Embodiment Collaboration, O'Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 111

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Visual adversarial imitation learning using variational models

Rafailov, R., Yu, T., Rajeswaran, A., & Finn, C. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 12

Scaling Robot Learning with Semantically Imagined Experience

Yu, T., Xiao, T., Stone, A., Tompson, J., Brohan, A., Wang, S., Singh, J., Tan, C., M, D., Peralta, J., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 4