3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Exploring Weak-to-Strong Generalization for CLIP-based Classification
Jinhao Li, Sarah M. Erfani, Lei Feng +2
Aligning large-scale commercial models with user intent is crucial to preventing harmful outputs. Current methods rely on human supervision but become impractical as model complexi…
Attribute-based Visual Reprogramming for Vision-Language Models
Chengyi Cai, Zesheng Ye, Lei Feng +2
Visual reprogramming (VR) reuses pre-trained vision models for downstream image classification tasks by adding trainable noise patterns to inputs. When applied to vision-language m…
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
Jinhao Li, Haopeng Li, Sarah Erfani +3
It has recently been discovered that using a pre-trained vision-language model (VLM), e.g., CLIP, to align a whole query image with several finer text descriptions generated by a l…
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
Yuwei Niu, Shuo He, Qi Wei +3
While multimodal contrastive learning methods (e.g., CLIP) can achieve impressive zero-shot classification performance, recent research has revealed that these methods are vulnerab…