A second-stage model that reorders retrieved chunks for precision.
1 min readupdated 2026-07-04
/ quick answer
A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency. A second-stage model that reorders retrieved chunks for precision.
A second-stage model that reorders retrieved chunks for precision. A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency. In practice: Retriever returns 50 candidates; the reranker keeps the top 5 with the strongest semantic match. This dictionary node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Definition
A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency.
Example
Retriever returns 50 candidates; the reranker keeps the top 5 with the strongest semantic match.
A reranker (typically a cross-encoder like Cohere Rerank or BGE) takes the top-N results from a first-stage retriever and re-scores them against the query, boosting precision at the cost of latency.
What is an example of Reranker?
Retriever returns 50 candidates; the reranker keeps the top 5 with the strongest semantic match.
Why does Reranker matter for AI and automation?
A second-stage model that reorders retrieved chunks for precision. It connects to the workflows, prompts and tool stacks linked on this page, so you can move from definition to execution without leaving Onexial.