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Retrieval and RAG

What is Reranking?

Reordering candidates after initial retrieval

Reranking scores a reduced set of documents or passages again with a more precise model. A source may be retrieved yet still fall out before reaching the generator.

What Reranking means in GEO

In a RAG pipeline, publishing is not enough. A page must be discoverable, enter the candidate set and survive reranking.

Why it matters

Align each passage with a specific intent and avoid mixing incompatible answers in the same block.

What to check in practice

Identify the stage where the source disappears: access, initial retrieval, reranking, generator context or citation selection.

How it connects to other concepts

Reranking belongs to retrieval and rag. It is best analyzed alongside related terms because AI visibility depends on several stages and signals rather than one isolated optimization.

Common mistake

Blaming final copy when the document never reached the model that writes the answer.

Turn these concepts into metrics

Bee LLM tracks mentions, citations, position, sentiment and competitors across major AI engines.

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