Repurposing discarded supervised classification heads from vision models as semantic prototypes boosts post-hoc vision-language alignment methods on retrieval and zero/few-shot classification.
The key properties for us are1: • (NC1) Variability Collapse:The feature vectors x for all training samples belonging to a class i collapse to their class mean, or centroid,µ i
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Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling
Repurposing discarded supervised classification heads from vision models as semantic prototypes boosts post-hoc vision-language alignment methods on retrieval and zero/few-shot classification.