What is reranking and why is it used?

Reranking is a second-stage process that takes a candidate set returned by initial retrieval and rescores them using a more accurate but slower model, typically a cross-encoder. Initial retrieval finds 50 to 100 candidates quickly, then reranking narrows them to the top 5 to 10 most relevant. Reranking dramatically improves retrieval quality at modest cost.