Grounded generation gives a model source material, structured records, tool results, or retrieved passages that constrain and support the output. A strong workflow builds claims from evidence, retains links between statements and sources, and distinguishes direct support from interpretation.
Grounding is only as reliable as the evidence and retrieval process. Low-quality sources, inaccessible primary reporting, stale pages, citation laundering, and incorrect extraction can produce an answer that looks grounded while still lacking credible support.
ELI5
Grounded generation means asking an AI to build its answer from evidence that has been supplied or retrieved for the task. It is similar to answering an open-book question and showing which pages support the answer instead of relying only on memory.
For example, a support assistant could read the latest product manual before explaining how to reset a device. The answer is more dependable when it stays close to that manual, although wrong, outdated, or poorly retrieved evidence can still lead to a wrong result.
How does grounded generation reduce hallucination?
It gives the model relevant evidence to use and allows important statements to be traced back to explicit sources.
Can grounded generation still be wrong?
Yes. The evidence may be weak, the retrieval may omit key sources, or the model may misinterpret what a source says.
