Rlprompt: Optimizing discrete text prompts with reinforcement learning M Deng, J Wang, CP Hsieh, Y Wang, H Guo, T Shu, M Song, EP Xing, ... arXiv preprint arXiv:2205.12548, 2022 | 257 | 2022 |
CERN: Confidence-Energy Recurrent Network for Group Activity Recognition T Shu, S Todorovic, SC Zhu IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 217 | 2017 |
Joint Inference of Groups, Events and Human Roles in Aerial Videos T Shu, D Xie, B Rothrock, S Todorovic, SC Zhu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015 | 211 | 2015 |
Hierarchical and Interpretable Skill Acquisition in Multi-task Reinforcement Learning T Shu, C Xiong, R Socher 6th International Conference on Learning Representations (ICLR), 2018 | 172 | 2018 |
Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration X Puig, T Shu, S Li, Z Wang, YH Liao, JB Tenenbaum, S Fidler, A Torralba The Ninth International Conference on Learning Representations, 2021 | 115 | 2021 |
Learning and inferring “dark matter” and predicting human intents and trajectories in videos D Xie, T Shu, S Todorovic, SC Zhu IEEE transactions on pattern analysis and machine intelligence 40 (7), 1639-1652, 2017 | 83* | 2017 |
AGENT: A Benchmark for Core Psychological Reasoning T Shu, A Bhandwaldar, C Gan, KA Smith, S Liu, D Gutfreund, E Spelke, ... The Thirty-eighth International Conference on Machine Learning (ICML), 2021 | 77 | 2021 |
Active visual information gathering for vision-language navigation H Wang, W Wang, T Shu, W Liang, J Shen Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 76 | 2020 |
Learning Social Affordance for Human-Robot Interaction T Shu, MS Ryoo, SC Zhu The 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016, 2016 | 73 | 2016 |
Vrkitchen: an interactive 3d virtual environment for task-oriented learning X Gao, R Gong, T Shu, X Xie, S Wang, SC Zhu arXiv preprint arXiv:1903.05757, 2019 | 71 | 2019 |
Where and why are they looking? jointly inferring human attention and intentions in complex tasks P Wei, Y Liu, T Shu, N Zheng, SC Zhu Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 68 | 2018 |
Language models meet world models: Embodied experiences enhance language models J Xiang, T Tao, Y Gu, T Shu, Z Wang, Z Yang, Z Hu Advances in neural information processing systems 36, 2024 | 61 | 2024 |
M^3RL: Mind-aware Multi-agent Management Reinforcement Learning T Shu, Y Tian 7th International Conference on Learning Representations (ICLR), 2019 | 59 | 2019 |
Building cooperative embodied agents modularly with large language models H Zhang, W Du, J Shan, Q Zhou, Y Du, JB Tenenbaum, T Shu, C Gan arXiv preprint arXiv:2307.02485, 2023 | 53 | 2023 |
Learning Social Affordance Grammar from Videos: Transferring Human Interactions to Human-Robot Interactions T Shu, X Gao, MS Ryoo, SC Zhu The IEEE International Conference on Robotics and Automation (ICRA), 2017, 2017 | 50 | 2017 |
Joint mind modeling for explanation generation in complex human-robot collaborative tasks X Gao, R Gong, Y Zhao, S Wang, T Shu, SC Zhu 2020 29th IEEE international conference on robot and human interactive …, 2020 | 46 | 2020 |
PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception A Netanyahu, T Shu, B Katz, A Barbu, JB Tenenbaum 35th AAAI Conference on Artificial Intelligence (AAAI), 2021 | 31 | 2021 |
Perception of human interaction based on motion trajectories: From aerial videos to decontextualized animations T Shu, Y Peng, L Fan, H Lu, SC Zhu Topics in cognitive science 10 (1), 225-241, 2018 | 26 | 2018 |
Social interactions as recursive mdps R Tejwani, YL Kuo, T Shu, B Katz, A Barbu Conference on Robot Learning, 949-958, 2022 | 24 | 2022 |
Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics T Shu, M Kryven, TD Ullman, JB Tenenbaum 42nd Annual Meeting of the Cognitive Science Society (CogSci), 2020 | 23 | 2020 |