
Supervised fine-tuning can effectively enhance the generalization capabilities of vision foundation models after pretraining.


coremsg

enhancing-visual-foundation-models-through-supervised-fine-tuning


Enhancing Visual Foundation Models through Supervised Fine-Tuning


title_rewrite


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.


masked-token-modeling-improves-storage-efficient-training-of-vision-transformers


Masked Token Modeling Improves Storage-efficient Training of Vision Transformers
