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AI & Machine Learning · Intermediate

Reranking

Re-scoring an initial set of retrieved results with a more accurate model to put the most relevant first.

Definition

A fast retriever fetches many candidates, then a cross-encoder or reranker model scores each query-document pair precisely. Reranking improves RAG precision and lets fewer, better chunks enter the context. Examples include Cohere Rerank, Amazon Bedrock rerank models, Azure AI Search semantic ranker and NVIDIA NeMo Retriever reranking NIM.

Exam tip

Add a reranker when relevant documents are retrieved but ranked too low.

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