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.
We use the Places365 validation set (50 images per class) instead of the larger test set (900 images per class) for computational efficiency
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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.