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Reranking search results models

31 in the catalogue today. Every one with what it costs, who sells it and where it stands.

Models that take a handful of results a search already found and put them in the right order. They are the cheap second stage of retrieval: an embedding search casts a wide net fast, a reranker reads the candidates properly. Because they only ever see a few documents, they cost little per query, and they usually improve a weak search more than a better embedding model would.