# SOLAR

Single-cell reference mapping no longer lets class representatives drift during training. SCLSC built each type representative from a mean expression profile, so its position moved as optimization proceeded; SOLAR assigns every reference label a fixed orthogonal direction before training and lets the encoder learn only where cells land in that space. Across nine held-out batches from human immune, lung and pancreas datasets at 30 dimensions, mean query macro-F1 was 0.811, above 0.774 for matched PCA and below 0.838 for scANVI.

Single-cell reference mapping no longer lets class representatives drift during training. SCLSC built each type representative from a mean expression profile, so its position moved as optimization proceeded; SOLAR assigns every reference label a fixed orthogonal direction before training and lets the encoder learn only where cells land in that space. Across nine held-out batches from human immune, lung and pancreas datasets at 30 dimensions, mean query macro-F1 was 0.811, above 0.774 for matched PCA and below 0.838 for scANVI.