6.2 Future Directions in Mitigation Methods

General and robust data pre-processing approaches. Since the data format varies between down-
stream tasks, there is still a gap for data processing methods between tasks, and currently, no
universal method is effective for all NLG tasks [101]. Data pre-processing might result in gram-
matical errors or semantic transformation between the original and processed data, which can
negatively affect the performance of generation. Therefore, we believe that general and robust data
pre-processing methods can help mitigate the hallucinations in NLG.
SurveyofHallucinationinNatural Language Generation