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What is re-ranking in RAG? How does a CrossEncoder improve retrieval quality?
Initial top-k vector retrieval can return chunks that are semantically similar but not truly relevant. A CrossEncoder jointly processes the query and each candidate chunk through a model to score real relevance, reordering results — plugged in via a DocumentPostProcessor in RetrievalAugmentationAdvisor.
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What is re-ranking in RAG? How does a CrossEncoder improve retrieval quality?