Haotian Liang — accepted AI-conference papers

2026

MM-ACT: Learn from Multimodal Parallel Generation to Act

Haotian Liang, Xinyi Chen, Bin Wang, Mingkang Chen, Yitian Liu, Yuhao Zhang +9

CVPR 2026

A generalist robotic policy needs both semantic understanding for task planning and the ability to interact with the environment through predictive capabilities. To tackle this, we present MM-ACT, a unified Vision-Language-Action (VLA) model that integrates text, image, and action in shared token sp

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2025

OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis

Junting Chen, Haotian Liang, Lingxiao Du, Weiyun Wang, Mengkang Hu, Yao Mu +5

NeurIPS 2025poster

The rapid progress of navigation, manipulation, and vision models has made mobile manipulators capable in many specialized tasks. However, the open-world mobile manipulation (OWMM) task remains a challenge due to the need for generalization to open-ended instructions and environments, as well as th…

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