Generation & Quality

What Is Abstention in AI Answers?

When an AI assistant declines to answer because its sources don't cover the question, and says so plainly instead of writing a confident guess.

An assistant that answers every question will sometimes answer questions its sources never covered. Abstention is the opposite: when retrieval finds nothing that addresses the question, the assistant says it doesn't know instead of writing a fluent guess. It is the main defence against hallucination in a customer-facing assistant.

Most systems ask for abstention in the prompt ("if the context doesn't answer, say you don't know"). Models follow that most of the time, not every time, because they are still handed the nearest pages, which share the subject without answering the question. Enforced abstention takes the decision out of the prompt: if retrieval judges that nothing answers the question, the model never sees those pages.

Too much abstention is also a failure, so it depends on a good relevance judgment, usually from a reranker. Done well, every abstention is useful data: it marks a knowledge gap, a real question your content can't answer yet.

How Kelu uses this

Every Kelu answer gets a coverage verdict after reranking: answerable, partial or not covered. On a not-covered verdict, an abstention gate withholds both the excerpts and the citations, so the model has nothing to guess from and tells the reader the question isn't covered. A partial answer says plainly what is missing. The gate runs on every answering surface, and abstained questions show up in the Coverage Gaps report.

From definition to deployment

Connect a knowledge source and see cited AI answers on your own content in minutes — free, no credit card required.

Free to start · No credit card required