Skip Tuning adapts CLIP by fine-tuning only the deep layers on a sampled subset of class tokens per image, beating prompt tuning and adapters in accuracy and efficiency.
Generalized meta-fdmixup: Cross-domain few-shot learning guided by labeled target data
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Skip Tuning: Pre-trained Vision-Language Models are Effective and Efficient Adapters Themselves
Skip Tuning adapts CLIP by fine-tuning only the deep layers on a sampled subset of class tokens per image, beating prompt tuning and adapters in accuracy and efficiency.