Innate divergence. Some NLG tasks by nature do not always have factual knowledge alignment
between the source input text and the target reference, especially those that value diversity in
generated output. For instance, it is acceptable for open-domain dialogue systems to respond in
chit-chat style, subjective style [152], or with a relevant fact that is not necessarily present in the
user input, history or provided knowledge source – this improves the engagingness and diversity
of the dialogue generation. However, researchers have discovered that such dataset characteristic
leads to inevitable extrinsic hallucinations.
SurveyofHallucinationinNatural Language Generation