Author

Fang Li

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Preprint Oct 2026

OmniBrain-0: A Unified Agentic Model for Embodied Intelligence

General-purpose embodied intelligence requires robots to coordinate diverse skills over long horizons, track task progress, and recover from failures. Specialist policies alone do not ensure task-level reliability, while powerful multimodal agents rely on costly reasoning and external experience that compact models str...

Xiaomi Embodied Intelligence Team Yuechen Luo, Chong He, Fang Li et al. · 0 citations

Preprint Aug 2026

One Policy, Many Embodiments: Unified Camera-Centric Action Geometry Pre-training for Heterogeneous Embodied Manipulation

UCAG-P is introduced, a camera-centric unified action formulation that structurally aligns heterogeneous embodied datasets into a shared geometric action space, and allows a shared VLA policy to learn transferable manipulation geometry while retaining embodiment-specific controllability.

Xiaomi Embodied Intelligence Team, University of Macau Shaoqing Xu, Fang Li et al. · 0 citations

Jul 2026

GeoWorldAD: Geometry World Action Model for Autonomous Driving

GeoWorldAD is proposed, a geometry world action model that grounds trajectory planning in ego-aligned 3D space and anticipates short-horizon scene evolution with latent future geometry tokens and progressively aggregates multi-scale present geometry and latent future geometry through iterative trajectory refinement.

Song-Yan Zhang, Jin-Yu Tian, Han-Bing Li et al. · arXiv.org · 1 citation