Unverified50% confidenceFactExact time
Reranking uses a cross-encoder to score query-document pairs one by one, with accuracy far higher than vector similarity but at higher computational cost, so fine ranking is done only on the small number of candidates after coarse ranking, forming a two-stage architecture of coarse ranking plus fine ranking.
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10/13/2026
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Unverified重排序通常使用交叉编码器实现，将查询和候选文档拼接后同时输入，通常只对Top-50到Top-100候选重排，最终选取Top-3到Top-5送入生成模型80% similarUnverifiedA Cross-Encoder concatenates the query and candidate code snippet before feeding them together as input, achieving higher scoring accuracy than a Bi-Encoder but at greater computational cost, so it is typically used only to re-rank the Top-K candidates recalled by ANN.78% similarUnverified重排阶段通常对10-50条候选文档进行精排，能够捕捉双编码器遗漏的细微语义关联从而提升检索相关性76% similarUnverifiedThe computational complexity of cross-encoders is O(n²); document representations cannot be precomputed and scoring must be done online pair by pair, so cross-encoders are typically only used to rerank the top-k results returned by an initial retrieval stage.75% similarVerified重排序（Re-ranking）机制在初步检索后引入交叉编码器（Cross-Encoder）对候选文档重新打分，提升输入大模型的上下文质量75% similar
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