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[ICML 2024] Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models

License: MIT License

Python 100.00%
deep-learning image-text-matching large-language-models similarity-score textual-prompting vision-language-model visual-prompting visual-text-alignment zero-shot-classification

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The results I obtained differ from those reported in the article.

Thank you for your outstanding work. After running your released code (with default parameter settings), I found significant discrepancies between my results and those reported in the paper. I tried several different random seeds, but the discrepancies persisted. For instance, for the ViT/B-32 model on the ImageNet dataset, the accuracies for different methods are as follows: {'clip': 60.83, 'clip-e': 62.20, 'clip-d': 61.88, 'waffe': 61.95, 'cupl': 63.25, 'ours': 61.21}. I'm unsure whether the issue lies with the code or my execution.

link error in data/README.md

Your research work is impressive!
BUT
Is there anything wrong about the link of the ImageNet-R?
Beacuse it may be same as the link of oxford-iiit-pet

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