| Learning the signatures of the human grasp using a scalable tactile glove S Sundaram, P Kellnhofer, Y Li, JY Zhu, A Torralba, W Matusik Nature 569 (7758), 698-702, 2019 | 1060 | 2019 |
| Open X-Embodiment: Robotic Learning Datasets and RT-X Models A Padalkar, A Pooley, A Jain, A Bewley, A Herzog, A Irpan, A Khazatsky, ... International Conference on Robotics and Automation (ICRA), 2023 | 605* | 2023 |
| CLEVRER: Collision Events for Video Representation and Reasoning K Yi, C Gan, Y Li, P Kohli, J Wu, A Torralba, JB Tenenbaum International Conference on Learning Representations (ICLR), 2020 | 536 | 2020 |
| InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations Y Li, J Song, S Ermon Advances in Neural Information Processing Systems (NIPS), 2017 | 511 | 2017 |
| VoxPoser: Composable 3D Value Maps for Robotic Manipulation with Language Models W Huang, C Wang, R Zhang, Y Li, J Wu, L Fei-Fei Conference on Robot Learning (CoRL), 2023 | 507 | 2023 |
| Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids Y Li, J Wu, R Tedrake, JB Tenenbaum, A Torralba International Conference on Learning Representations (ICLR), 2019 | 416 | 2019 |
| Learning human–environment interactions using conformal tactile textiles Y Luo, Y Li, P Sharma, W Shou, K Wu, M Foshey, B Li, T Palacios, ... Nature Electronics 4 (3), 193-201, 2021 | 307 | 2021 |
| BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation C Li, R Zhang, J Wong, C Gokmen, S Srivastava, R Martín-Martín, C Wang, ... arXiv preprint arXiv:2403.09227, 2024 | 197* | 2024 |
| Face Detection with End-to-End Integration of a ConvNet and a 3D Model Y Li, B Sun, T Wu, Y Wang European Conference on Computer Vision (ECCV), 420-436, 2016 | 175 | 2016 |
| Propagation Networks for Model-Based Control Under Partial Observation Y Li, J Wu, JY Zhu, JB Tenenbaum, A Torralba, R Tedrake International Conference on Robotics and Automation (ICRA), 2019 | 166 | 2019 |
| 3D Neural Scene Representations for Visuomotor Control Y Li, S Li, V Sitzmann, P Agrawal, A Torralba Conference on Robot Learning (CoRL), 2021 | 151 | 2021 |
| Learning Compositional Koopman Operators for Model-Based Control Y Li, H He, J Wu, D Katabi, A Torralba International Conference on Learning Representations (ICLR), 2020 | 144 | 2020 |
| Connecting Touch and Vision via Cross-Modal Prediction Y Li, JY Zhu, R Tedrake, A Torralba Computer Vision and Pattern Recognition (CVPR), 2019 | 140 | 2019 |
| Causal Discovery in Physical Systems from Videos Y Li, A Torralba, A Anandkumar, D Fox, A Garg Neural Information Processing Systems (NeurIPS), 2020 | 124 | 2020 |
| Executable Code Actions Elicit Better LLM Agents X Wang, Y Chen, L Yuan, Y Zhang, Y Li, H Peng, H Ji International Conference on Machine Learning (ICML), 2024 | 120 | 2024 |
| Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning L Manuelli, Y Li, P Florence, R Tedrake Conference on Robot Learning (CoRL), 2020 | 113 | 2020 |
| Learning Physical Graph Representations from Visual Scenes DM Bear, C Fan, D Mrowca, Y Li, S Alter, A Nayebi, J Schwartz, L Fei-Fei, ... Neural Information Processing Systems (NeurIPS), 2020 | 96 | 2020 |
| Learning Multi-Object Dynamics with Compositional Neural Radiance Fields D Driess, Z Huang, Y Li, R Tedrake, M Toussaint Conference on Robot Learning (CoRL), 2022 | 92 | 2022 |
| Visual Grounding of Learned Physical Models Y Li, T Lin, K Yi, D Bear, DLK Yamins, J Wu, JB Tenenbaum, A Torralba International Conference on Machine Learning (ICML), 2020 | 79 | 2020 |
| RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks H Shi, H Xu, Z Huang, Y Li, J Wu Robotics: Science and Systems (RSS), 2022 | 78 | 2022 |
Antonio TorralbaProfessor of Computer Science, MITE-mail confirmado em csail.mit.edu
