Publications and Preprints
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Theia: Distilling Diverse Vision Foundation Models for Robot Learning
Jinghuan Shang, Karl Schmeckpeper, Brandon B. May, Maria Vittoria Minniti, Tarik Kelestemur, David Watkins, Laura Herlant CoRL 2024 [Project Page] [arXiv] [Demo] 
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Continual Learning with Global Alignment
Xueying Bai, Jinghuan Shang, Yifan Sun, Niranjan Balasubramanian NeurIPS 2024 Paper coming soon. |
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LLaRA: Supercharging Robot Learning Data for Vision-Language Policy
Xiang Li, Cristina Mata, Jongwoo Park, Kumara Kahatapitiya, Yoo Sung Jang, Jinghuan Shang, Kanchana Ranasinghe, Ryan Burgert, Mu Cai, Yong Jae Lee, and Michael S. Ryoo arXiv [arXiv] 
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Crossway Diffusion: Improving Diffusion-based Visuomotor Policy via Self-supervised Learning
Xiang Li, Varun Belagali, Jinghuan Shang and Michael S. Ryoo ICRA 2024 [arXiv] 
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Active Vision Reinforcement Learning under Limited Visual Observability
Jinghuan Shang and Michael S. Ryoo NeurIPS 2023 [Project Page] [arXiv] 
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Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space
Jinghuan Shang, Srijan Das, and Michael S. Ryoo NeurIPS 2022 [Project Page] [arXiv] 
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Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li, Jinghuan Shang, Srijan Das, and Michael S. Ryoo NeurIPS 2022 [arXiv] |
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Neural Neural Textures Make Sim2Real Consistent
, Jinghuan Shang, Xiang Li, and Michael S. Ryoo CoRL 2022 [Project Page] [Code] [arXiv] |
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StARformer: Transformer with State-Action-Reward Representations for Robot Learning
Jinghuan Shang, Xiang Li, Kumara Kahatapitiya, Yu-Cheol Lee, Michael S. Ryoo IEEE TPAMI, Special Issue on Transformer Models in Vision, 2022 [PDF] [IEEE Xplore] 
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StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
Jinghuan Shang, Kumara Kahatapitiya, Xiang Li, and Michael S. Ryoo ECCV 2022 [arXiv] [Video] [Poster]
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Self-Supervised Disentangled Representation Learning for Third-Person Imitation Learning
Jinghuan Shang and Michael S. Ryoo IROS 2021 [arXiv] [Talk] [Digest Slide] |
