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.
Representation Learning Generalized Contrastive Learning Embedding Sizes Minimal Impact Original Embedding
Source: marqo.ai