LUViT jointly pretrains a ViT with masked auto-encoding and LoRA adapters in a frozen LLM block, reporting +0.4% ImageNet-1K accuracy and up to +2.2% on ImageNet-A over its own MAE baseline.
In these works, they provided litmus tests for measuring how focused the attention patterns of particular models are and how they relate to model robustness
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Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs
LUViT jointly pretrains a ViT with masked auto-encoding and LoRA adapters in a frozen LLM block, reporting +0.4% ImageNet-1K accuracy and up to +2.2% on ImageNet-A over its own MAE baseline.