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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.
Sources coveringTowards Data Science, arXiv, AWS, Fortune
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

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

Towards Data Science1 min read

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.

Read the full article at Towards Data Science

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