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Author

Lijing Lin

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Open access Sep 2026

NexuST: A Hierarchical Foundation Model for Spatial Transcriptomics

Spatial transcriptomics captures molecular states within cells and their organisation in tissue. However, integrating fine-grained gene information with spatial context at scale remains challenging for existing foundation models. Here we present NexuST, a hierarchical foundation model that repeatedly interleaves gene-l...

Hai-Ping Liu, Qian Zhao, Li-Jing Lin et al. · 0 citations
Preprint Aug 2026

CellWorld: From Gene-Level Reconstruction to Latent Cell Prediction in Spatial Transcriptomics Foundation Models

This paper shows that latent-space predictive pretraining can provide a scalable route to foundation models for spatial transcriptomics. Existing spatial transcriptomics foundation models primarily reconstruct masked gene identities or expression values, potentially encouraging the reproduction of assay-specific techni...

Hai-Ping Liu, Qian Zhao, Li-Jing Lin et al. · 0 citations

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