Re-Weighting Cross-Modal Pairs via Rank Consistency for Noise-Robust Retrieval
Image-text alignment relies on large-scale, well-aligned image-text pairs, yet web-crawled datasets inevitably introduce noisy correspondence. Existing methods typically re-weight training pairs by estimating semantic matching degrees from the model's own similarity predictions, which are inherently unreliable under no...