Publications and Preprints
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VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing
Yixiao Wang, Mingxiao Huo, Zhixuan Liang, Yushi Du, Lingfeng Sun, Haotian Lin, Jinghuan Shang, Chensheng Peng, Mohit Bansal, Mingyu Ding, Masayoshi Tomizuka ICLR 2026 [Paper] [arXiv] |
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Sceniris: a Fast Procedural Scene Generation Framework
Jinghuan Shang, Harsh Patel, Ran Gong, Karl Schmeckpeper Pre-print 2025 [arXiv] 
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AnyTask: an Automated Task and Data Generation Framework for Advancing Sim-to-Real Policy Learning
Ran Gong*, Xiaohan Zhang*, Jinghuan Shang*, Maria Vittoria Minniti*, Jigarkumar Patel, Valerio Pepe, Riedana Yan, Ahmet Gundogdu, Ivan Kapelyukh, Ali Abbas, Xiaoqiang Yan, Harsh Patel, Laura Herlant, Karl Schmeckpeper *The first four authors contributed equally Pre-print 2025 [Project Page] [arXiv] |
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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] [Code] |
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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 ICLR 2025; Spotlight at LangRob@CoRL, 2024 [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] |
