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mediumAI Engineering

What is reranking and why add it after retrieval?

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01

Understand the problem

Cross-encoders as a precision stage: cheap recall first, expensive relevance second.

rerankingcross-encoderretrievalrag
02

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Nudge consolestandby

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03

Study the solution

A reranker is a cross-encoder model that scores each (query, document) pair jointly — far more accurate than comparing precomputed embeddings, but too slow to run over the whole corpus. So RAG pipelines do two stages: fast ANN/hybrid retrieval pulls top-50/100 candidates (recall), then the reranker reorders them and yo

Solution ready — 2 min read

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04

Read the code

Two-stage retrieval with a score floor
const candidates = await hybridSearch(query, { limit: 80 });

const scored = await reranker.rank({
  query,
  documents: candidates.map((c) => c.text),
  topN: 8,
});

const kept = scored.filter((r) => r.relevance > 0.35);   // calibrated floor
if (kept.length === 0) return abstain();                 // no junk context
return kept.map((r) => candidates[r.index]);
05

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