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Preprint Aug 2026

Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views

The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expression values. This objective encourages these models to learn gene dependencies but does not directly optimize whole-cell representations, which are essential for many...

Jiaqi Xiong, Yun-Tao Hu, Yu Zheng et al. · 0 citations
Open access Aug 2026

Interatomic Potential Prediction Based on Charge Equilibration and Equivariant Transformer

Conventional local machine-learning interatomic potentials describe atomic environments with a finite cutoff radius and therefore have difficulty capturing long-range electrostatic coupling in polar, charged, or charge-transfer systems. This paper proposes CE-ETNet (Charge-Equilibration-Enhanced Equivariant Transformer...

Yifei Shi, Tao Luo · 0 citations

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