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洞見 - Vision model training
Enhancing Visual Foundation Models through Supervised Fine-Tuning
Supervised fine-tuning can effectively enhance the generalization capabilities of vision foundation models after pretraining.
Masked Token Modeling Improves Storage-efficient Training of Vision Transformers
Masked Token Modeling (MTM) can improve the storage efficiency of token-based vision model training by leveraging self-supervised pre-training, while TokenAdapt and ColorAdapt enhance the effectiveness of token-based data augmentation.
