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How AI Answers Questions About Documents It Never Learned

1Why the Model Cannot Answer From Your Documents Alone2Chunking and Embedding: Turning Documents Into Something Searchable3Retrieval: Finding the Right Passages for a Question4Grounded Generation: Answering From the Retrieved Text
Why the Model Cannot Answer From Your Documents Alone

A Confident Answer With Nothing Behind It

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Here is a question about a document the model has never seen: what does our internal policy say about remote work on Fridays?
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When a language model is asked about a document it never saw during training, it does not stay silent. It generates a fluent answer anyway, because generation always continues the text. The answer may sound authoritative while resting on no source at all. This is the failure mode that retrieval-augmented generation is designed to remove.

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