Sermanet, Pierre
Q
15 papers on CoChat
Most cited papers
- Verified
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques
Cited by 48,562
- Verified
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., & LeCun, Y. (2013) · arXiv
Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques
Cited by 2,680
- Verified
Going Deeper with Convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2014) · arXiv
Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques
Cited by 1,461
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Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Ahn, M., Brohan, A., Brown, N., Chebotar, Y., Cortes, O., David, B., Finn, C., Fu, C., Gopalakrishnan, K., Hausman, K., et al. (2022) · arXiv
Smart Agriculture and AIAI-based Problem Solving and Planning
Cited by 624
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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
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With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Dwibedi, D., Aytar, Y., Tompson, J., Sermanet, P., & Zisserman, A. (2021) · arXiv
Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications
Cited by 405
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With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Dwibedi, D., Aytar, Y., Tompson, J., Sermanet, P., & Zisserman, A. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications
Cited by 404
- Verified
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
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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
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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
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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
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RT-H: Action Hierarchies Using Language
Belkhale, S., Ding, T., Xiao, T., Sermanet, P., Vuong, Q., Tompson, J., Chebotar, Y., Dwibedi, D., & Sadigh, D. (2024) · arXiv
AI-based Problem Solving and PlanningNatural Language Processing Techniques
Cited by 71
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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
- Verified
Language Conditioned Imitation Learning over Unstructured Data
Lynch, C., & Sermanet, P. (2020) · arXiv
Reinforcement Learning in RoboticsRobot Manipulation and Learning
Cited by 18
- Verified
Gemini Robotics: Bringing AI into the Physical World
Gemini Robotics Team, Abeyruwan, S., Ainslie, J., Alayrac, J.-B., Arenas, M. G., Armstrong, T., Balakrishna, A., Baruch, R., Bauza, M., Blokzijl, M., et al. (2025) · arXiv
Robot Manipulation and LearningMultimodal Machine Learning Applications
Cited by 8
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