Currently there are many active efforts to address hallucination for various NLG tasks. Analyzing
hallucinatory content in different NLG tasks and investigating their relationship would strengthen
our understanding of this phenomenon and encourage the unification of efforts from different
NLG fields. However, to date, little has been done to understand hallucinations from a broader
perspective that encompasses all major NLG tasks. To the best of our knowledge, existing surveys
have only focused specific tasks like abstractive summarization [76, 125] and translation [95]. Thus,
in this paper, we present a survey of the research progress and challenges in the hallucination
problem in NLG. And offer a comprehensive analysis of existing research on the phenomenon
of hallucination in different NLG tasks, namely abstractive summarization, dialogue generation,
generative question answering, data-to-text generation, machine translation. We mainly discussed
SurveyofHallucinationinNatural Language Generation