Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness
Published in Preprint, 2023
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.
Recommended citation: Rawte, V., Priya, P., Tonmoy, S.M., Zaman, S.M., Sheth, A. and Das, A., 2023. Exploring the relationship between llm hallucinations and prompt linguistic nuances: Readability, formality, and concreteness. arXiv preprint arXiv:2309.11064.