Cascading retrieval with multi-vector representations: balancing efficiency and effectiveness | Pinecone

This blog post explores how multi-vector retrieval improves search accuracy by capturing rich query-document interactions, while addressing its scalability challenges. It introduces a practical, staged retrieval pipeline that balances speed and effectiveness, starting with fast retrieval, refining with multi-vector embeddings, and finishing with cross-encoder reranking. The post highlights ConstBERT, a constant-space multi-vector model co-developed by Pinecone and academic collaborators, and shows how to integrate it into Pinecone to build efficient, scalable, and accurate search systems. ConstBERT is now available in open source.

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