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Fang Li

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#artificial intelligence Preprint Oct 2026

GeoGR: Spatial-Semantic Token Compression and Group Routing for Efficient 3D VLMs

Multi-view representations enable pretrained image and video vision-language models to understand 3D scenes, but their long visual token sequences make inference costly. Redundancy arises both from repeated observations of the same scene regions across views and from processing all visual tokens at every LLM layer, reg...

Yong-Xing Zheng, Hao Wu, Fang Li et al. · 0 citations
Preprint Aug 2026

Energy-Guided Flow Matching

Energy-Guided Flow Matching is introduced that explicitly models a coarse-to-fine generative trajectory by moving endpoint that evolves smoothly from low-frequency image to clean image and requires no adaptation of the backbone and training data.

Haoyang Tong, Yu He, Fang Li et al. · 0 citations

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