Decoder. plain-English AI glossary

Citation Grounding

▲ Rising

Also called Answer Attribution

Making the model point to the exact source for each claim, so answers are checkable.

Think of it like

A term paper with footnotes — you can flip to the reference and confirm the writer didn’t make it up.

Example

A research assistant answers "revenue grew 12%" with a clickable link to the sentence in the 10-K that says so.

How it actually works

Citation grounding ties each generated statement back to a retrieved passage, usually by having the model reference chunk IDs it was given. It boosts trust and makes hallucinations catchable, since a claim with no supporting source is a red flag. The hard part is faithfulness — models can cite a source that doesn’t actually support the claim, so citations reduce but do not eliminate the need to verify.

For product teams

The feature that turns "trust me" into "check for yourself"; a big driver of user trust in RAG.

For engineers

Claim-to-chunk linking via referenced IDs; improves verifiability but citation faithfulness itself must be checked.

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