CellRefine adds a marker-gene-guided post-pretraining stage to single-cell models that refines the cell embedding manifold and improves downstream task performance by up to 15%.
scbert as a large-scale pretrained deep language model for cell type annotation of single-cell rna-seq data.Nature Machine Intelligence, 4(10):852–866
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A new benchmarking framework shows virtual cell models overestimate performance on standard tests, drop sharply on unseen contexts and perturbations, and produce inconsistent rankings across metrics.
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Prototype Guided Post-pretraining for Single-Cell Representation Learning
CellRefine adds a marker-gene-guided post-pretraining stage to single-cell models that refines the cell embedding manifold and improves downstream task performance by up to 15%.
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Benchmarking virtual cell models for in-the-wild perturbation response
A new benchmarking framework shows virtual cell models overestimate performance on standard tests, drop sharply on unseen contexts and perturbations, and produce inconsistent rankings across metrics.