As Large Language Models (LLMs) have advanced, they have brought forth new challenges, with one of the prominent issues being LLM hallucination. While various mitigation techniques are emerging to address hallucination, it is equally crucial to delve into its underlying causes. Consequently, in this preliminary exploratory investigation, we examine how linguistic factors in prompts, specifically readability, formality, and concreteness, influence the occurrence of hallucinations. Our experimental results suggest that prompts characterized by greater formality and concreteness tend to result in reduced hallucination. However, the outcomes pertaining to readability are somewhat inconclusive, showing a mixed pattern.

翻译：随着大型语言模型（LLMs）的进步，它们带来了新的挑战，其中一个突出问题便是LLM幻觉。尽管各种缓解技术正在涌现以应对幻觉问题，但深入探究其根本原因同样至关重要。因此，在这项初步的探索性研究中，我们考察了提示中的语言因素——具体而言是可读性、正式性和具体性——如何影响幻觉的发生。我们的实验结果表明，具有更高正式性和具体性的提示往往会导致幻觉减少。然而，关于可读性的结果有些不明确，呈现出混合的模式。