few-shot-transfer

This Texas A&M paper introduces "semantic recoverability" to explain which downstream tasks survive same-instance self-supervised learning, linking recoverability to class-distance-normalized variance, few-shot nearest-centroid transfer, and the spectral subspace spanned by cross-view-stable modes of the SSL objective.