Florence, Pete

Code as Policies: Language Model Programs for Embodied Control

Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., & Zeng, A. (2022) · arXiv

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 767

Code as Policies: Language Model Programs for Embodied Control

Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., & Zeng, A. (2023) · 2023 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 767

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

Towards Generalist Biomedical AI

Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2023) · arXiv

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 483

Towards Generalist Biomedical AI

Tu, T., Azizi, S., Driess, D., Schaekermann, M., Amin, M., Chang, P.-C., Carroll, A., Lau, C., Tanno, R., Ktena, I., et al. (2024) · NEJM AI

Artificial Intelligence in Healthcare and EducationMultimodal Machine Learning Applications

Cited by 483

Inner Monologue: Embodied Reasoning through Planning with Language Models

Huang, W., Xia, F., Xiao, T., Chan, H., Liang, J., Florence, P., Zeng, A., Tompson, J., Mordatch, I., Chebotar, Y., et al. (2022) · arXiv

AI-based Problem Solving and PlanningRobot Manipulation and Learning

Cited by 287

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

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Zeng, A., Attarian, M., Ichter, B., Choromanski, K., Wong, A., Welker, S., Tombari, F., Purohit, A., Ryoo, M., Sindhwani, V., et al. (2022) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 205

Transporter Networks: Rearranging the Visual World for Robotic Manipulation

Zeng, A., Florence, P., Tompson, J., Welker, S., Chien, J., Attarian, M., Armstrong, T., Krasin, I., Duong, D., Wahid, A., et al. (2020) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 200

Implicit Behavioral Cloning

Florence, P., Lynch, C., Zeng, A., Ramirez, O., Wahid, A., Downs, L., Wong, A., Lee, J., Mordatch, I., & Tompson, J. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 131

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks

Seita, D., Florence, P., Tompson, J., Coumans, E., Sindhwani, V., Goldberg, K., & Zeng, A. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 130

Interactive Language: Talking to Robots in Real Time

Lynch, C., Wahid, A., Tompson, J., Ding, T., Betker, J., Baruch, R., Armstrong, T., & Florence, P. (2022) · arXiv

Robot Manipulation and LearningSpeech and dialogue systems

Cited by 113

Large Language Models as General Pattern Machines

Mirchandani, S., Xia, F., Florence, P., Ichter, B., Driess, D., Arenas, M. G., Rao, K., Sadigh, D., & Zeng, A. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 49

XIRL: Cross-embodiment inverse reinforcement learning

Zakka, K., Zeng, A., Florence, P., Tompson, J., Bohg, J., & Dwibedi, D. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 38

Scaling Up and Distilling Down: Language-Guided Robot Skill Acquisition

Ha, H., Florence, P., & Song, S. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 24

ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation

ALOHA 2 Team, Aldaco, J., Armstrong, T., Baruch, R., Bingham, J., Chan, S., Draper, K., Dwibedi, D., Finn, C., Florence, P., et al. (2024) · arXiv

Teleoperation and Haptic SystemsRobot Manipulation and Learning

Cited by 8