SAVE is a conditional Transformer framework with gene block attention and flow matching that generates multi-condition single-cell data and generalizes better than prior methods to unseen condition combinations.
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SAVE: A Generalizable Framework for Multi-Condition Single-Cell Generation with Gene Block Attention
SAVE is a conditional Transformer framework with gene block attention and flow matching that generates multi-condition single-cell data and generalizes better than prior methods to unseen condition combinations.