Unverified50% confidenceFactExact time
Reranking means that after candidate documents are obtained through vector recall, a cross-encoder model re-scores and sorts the results to improve final relevance.
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50%
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Long-term
Relevance
10/27/2026
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UnverifiedRanking models perform fine-grained sorting on top of initially recalled results, pushing the most relevant content to the front.80% similarVerifiedReranking is the step of performing a secondary sort on retrieval results to improve relevance.78% similarVerifiedCross-Encoder reranking models can achieve more precise result ranking at the cost of higher computational overhead.77% similarVerifiedReranking uses a Cross-Encoder model to re-score and re-rank the candidate chunks recalled by Top-K, with precision far higher than that of a Bi-Encoder.76% similarUnverifiedReranking models score the query and document together, capturing finer-grained relevance signals, but inference must be run in real time at query time, resulting in higher latency.75% similar
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