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Matryoshka Representation Learning with CLIP for Multimodal Retrieval and Ranking

TL;DR We introduce Matryoshka Representation Learning (MRL), facilitating flexible embedding sizes in vector databases. This allows a balance between efficiency and granularity. Through MRL, embeddings condense into smaller dimensions while preserving performance in retrieval and ranking tasks. In summary, MRL empowers cost-effective flexibility without compromising performance in multimodal retrieval and ranking tasks.

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