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Rethinking Few-Shot Adaptation of Vision-Language Models in Two Stages
Matteo Farina, Massimiliano Mancini, Giovanni Iacca +1
An old-school recipe for training a classifier is to (i) learn a good feature extractor and (ii) optimize a linear layer atop. When only a handful of samples are available per cate…
Frustratingly Easy Test-Time Adaptation of Vision-Language Models
Matteo Farina, Gianni Franchi, Giovanni Iacca +2
Vision-Language Models seamlessly discriminate among arbitrary semantic categories, yet they still suffer from poor generalization when presented with challenging examples. For thi…
MULTIFLOW: Shifting Towards Task-Agnostic Vision-Language Pruning
Matteo Farina, Massimiliano Mancini, Elia Cunegatti +3
While excellent in transfer learning, Vision-Language models (VLMs) come with high computational costs due to their large number of parameters. To address this issue, removing para…