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Cascading retrieval: Unifying dense and sparse vector embeddings with reranking
New cascading retrieval capabilities make it seamless to combine dense retrieval and sparse retrieval and reranking into a unified search pipeline, delivering unparalleled precision, performance, and ease of use.
Yet, despite their precision, lexical methods have notable limitations, too—including the ability to understand semantic relationships, such as synonyms or paraphrases, that dense embeddings handle intuitively. Pinecone’s new capabilities allow systems to seamlessly combine dense and sparse retrieval, enabling search utilities that capture both semantic understanding and precise keyword matches. This approach improves retrieval for structured queries, such as part numbers or stock tickers, while avoiding irrelevant term expansions common in other sparse models.
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