What Is a Reranker? The Second-Stage Model That Improves Search Results
Unite.AI, Sunday, October 18th, 2026
A primer on rerankers, the second-stage models that reorder retrieved candidates for relevance in search and RAG.
The guide defines a reranker as a model that evaluates a small candidate set more deeply and reorders it after fast first-stage retrieval, unlike first-stage retrievers that must search the whole corpus quickly.
It treats retrieval as a pipeline of parsing, indexing, candidate generation, ranking, context assembly and answer generation, each of which can add or lose evidence.
Reranking improves precision but adds latency and cannot recover documents the first stage never retrieved.
For that reason, teams should trace and evaluate each stage.