А. Ю. Судаков

Learning Cross-Model Activation Alignments with Explicit Many-to-Many Layer Maps

This work studies an activation alignment, a map from a source model's layerwise activations to a target's, and factors this map into a layer map, whose output is an explicit target-by-source matrix that can be extracted and inspected, and a layer-shared feature map between hidden spaces.