Making AI Smarter at Understanding Images and Text
Embedding models often struggle with tricky mismatches between images and text, especially in hard negative pairs. This paper introduces a new regularization strategy that helps AI learn from these tough cases, leading to big improvements in tasks like image-text search and even zero-shot video retrieval. That means better AI for things like searching massive image libraries or automatically understanding video content—without extra training!
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