Enterprise Document Intelligence [Vol. 1 #9bis] - Your RAG isn’t hallucinating, it’s answering the wrong context faithfully.
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Enterprise Document Intelligence [Vol. 1 #7quinquies] - Hallucination is usually garbage-in.
Enterprise Document Intelligence [Vol. 1 #7quinquies] - Hallucination is usually garbage-in.
Enterprise Document Intelligence [Vol. 1 #4bis] - A coauthor note on the brick-by-brick pitfalls that justified the four-brick split, before Part II walks the fixes The post 10 Common RAG Mistakes We Keep Seeing in Production appeared first on Towards Data Science .
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.
Enterprise Document Intelligence [Vol. 1 #8A] - The schema is the contract: every field is a question the pipeline asks the model, and every answer is checkable The post Stop Returning Text from RAG: The Typed Answer Contract That Prevents Hallucination appeared first on Towards Data Science .
Enterprise Document Intelligence [Vol. 1 #M2] - Every RAG system is built in three engineering layers stacked on one LLM call: prompt (the call itself), context (what fills the model’s window), loop (when the next call fires and when it stops).