Glossary · Retrieval & generation
Dense Retrieval
First-stage retrieval that embeds queries and candidates into vector representations and ranks candidates by a similarity function.
Why it matters
It can retrieve paraphrases and semantic matches that share few exact words, complementing lexical methods such as BM25.
In practice
Train or select an embedding model for the domain, index candidate vectors, and evaluate retrieval recall before connecting the results to generation.
Common confusion
Dense retrieval is not a reranker. It searches the collection, while a reranker rescores a smaller candidate set.
Related terms
Sources
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