A hierarchical adversarial fine-tuning method for VLMs aligns image and text embeddings at multiple hierarchy depths with theoretical margin connections to boost robustness to leaf and superclass attacks while using multiple trees for semantic variety.
Pre-trained model guided fine-tuning for zero-shot adversarial robustness
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Hierarchically Robust Zero-shot Vision-language Models
A hierarchical adversarial fine-tuning method for VLMs aligns image and text embeddings at multiple hierarchy depths with theoretical margin connections to boost robustness to leaf and superclass attacks while using multiple trees for semantic variety.