datasets into long premise NLI datasets automatically. The results indicate that long-premise NLI
datasets help the model achieve a higher performance than the original NLI datasets. In addition,
Laban et al. [93] introduce a simple but efficient method called SUMMAC𝐶𝑜𝑛𝑣 by applying NLI
models to sentence units that are segmented from documents. The performance of their model is
better than applying NLI models to the whole document.
SurveyofHallucinationinNatural Language Generation