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COMPEL Glossary / naive-rag

Naive RAG

The baseline retrieval-augmented-generation pattern: a single retrieval step returns the top-k chunks by vector similarity, and those chunks are concatenated into the prompt for generation.

What this means in practice

Useful as a starting point; known to fail on multi-hop questions, long-tail queries, and cases where reranking or query rewriting would help.

Synonyms

vanilla RAG , single-pass RAG

Related Terms Network

This diagram shows how Naive RAG connects to other concepts in the COMPEL body of knowledge. Each linked node is a term you can explore in turn.

Related terms for Naive RAG Network graph showing 3 related glossary terms connected to Naive RAG. Naive RAG Hybrid ret… Reranker Agentic RA…
3 related concepts connected to Naive RAG.

The COMPEL Glossary Graph visualizes relationships between framework terminology, showing how concepts interconnect across domains, stages, and pillars. Term nodes cluster by pillar affiliation while cross-references reveal semantic dependencies — for example, how risk appetite connects to control effectiveness, model governance, and assurance requirements. This network representation helps practitioners navigate the framework vocabulary and understand that COMPEL terminology forms a coherent conceptual system rather than isolated definitions.

Accessible list of related terms
  • Hybrid retrieval — A retrieval pattern combining dense (vector-based, e.g., dense passage retrieval) and sparse (term-based, e.g., BM25) retrieval methods, whose candidate sets are fused — typically via reciprocal rank fusion — before reranking.
  • Reranker — A cross-encoder model that re-scores a candidate set of documents — typically the top-k from an initial vector or hybrid retrieval — to improve ordering by the actual query-document semantic match.
  • Agentic RAG — A retrieval pattern in which the agent decides — within its loop — when and what to retrieve, rather than a retrieval step running before generation as in naive RAG.

See also

  • Hybrid retrieval — A retrieval pattern combining dense (vector-based, e.g., dense passage retrieval) and sparse (term-based, e.g., BM25) retrieval methods, whose candidate sets are fused — typically via reciprocal rank fusion — before reranking.
  • Reranker — A cross-encoder model that re-scores a candidate set of documents — typically the top-k from an initial vector or hybrid retrieval — to improve ordering by the actual query-document semantic match.
  • Agentic RAG — A retrieval pattern in which the agent decides — within its loop — when and what to retrieve, rather than a retrieval step running before generation as in naive RAG.