Reranking: definition

Reranking is a second pass that reorders search or retrieval results by how well they actually answer the query, lifting the quality of what a RAG system shows the model.

Fast retrieval casts a wide net and is not always precise about ordering. A reranker takes the top candidates and scores them more carefully for relevance, so the few passages the model actually sees are the best ones.

It is a high-leverage, often-skipped step: better ordering of retrieved context usually improves answer quality more than swapping to a bigger model.

Related terms

Retrieval-augmented generation (RAG): Retrieval-augmented generation is a technique that fetches relevant passages from your own documents at question time and hands them to the model, so its answer is grounded in your data instead of its training.
Semantic search: Semantic search finds results by meaning rather than exact keywords, so a search for "cancel my plan" surfaces the "how to end your subscription" page even though they share no words.
Embeddings: An embedding is a list of numbers that captures the meaning of a piece of text, so that passages about similar things sit close together and can be found by similarity rather than exact words.