Reranking

Reranking is a second-stage scoring step that takes the top-K candidates returned by a fast initial retriever and reorders them using a more accurate but costlier model — typically a cross-encoder that jointly considers the query and each passage together. By separating the coarse retrieval stage from fine-grained relevance scoring, a reranker improves precision without sacrificing the scalability of the first-stage retriever.