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This article addresses Retrieval-Augmented Generation (RAG) by reframing common failures as extraction errors rather than hallucinations, proposing seven typed-contract patterns to enforce accuracy in small models. The core contribution lies in defining a decomposition rule that ensures generated answers strictly adhere to retrieved context without relying on large model capabilities for correction.

Surse care acoperăTowards Data Science, arXiv, AWS, Fortune

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Most RAG Hallucinations Are Extraction Errors: Seven Patterns for a Typed Generation Contract

Towards Data Science23 iulie 20261 min de cititArticolul și perspectiva sunt în engleză.

Enterprise Document Intelligence [Vol.1 #8ter] - Naming the RAG error correctly matters: model reads the context, so a wrong answer is an extraction error, not a hallucination. Seven typed-contract patterns keep the generation brick honest, with a decomposition rule for small models The post Most RAG Hallucinations Are Extraction Errors: Seven Patterns for a Typed Generation Contract appeared first on Towards Data Science.

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