Mind Your Tone: Does Tone Alter LLM Performance? 事件

Mind Your Tone: Does Tone Alter LLM Performance? arXiv:2605.29027v1 Announce Type: cross Abstract: The use of Large Language Models (LLMs) is proliferating, yet their performance is observed to vary based on prompting styles and tones. In this study, we investigate both whether and how tonal variations in prompts lead to disparate LLM accuracy for objective multiple-choice questions. We use two datasets: a 50-base question dataset with five tone variants and a 570-base question MMLU subset span