Bangguo Li — accepted AI-conference papers

2026

RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization

LIU SONGMING, Bangguo Li, Kai Ma, Lingxuan Wu, Hengkai Tan, Xiao Ouyang +2

ICML 2026poster

Vision-Language-Action (VLA) models hold promise for generalist robotics but currently struggle with data scarcity, architectural inefficiencies, and the inability to generalize across different hardware platforms. We introduce RDT2, a robotic foundation model built upon a 7B parameter VLM designed …

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2025

RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang +3

ICLR 2025poster

Bimanual manipulation is essential in robotics, yet developing foundation models is extremely challenging due to the inherent complexity of coordinating two robot arms (leading to multi-modal action distributions) and the scarcity of training data. In this paper, we present the Robotics Diffusion Tr…

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