Large Language Models (LLMs) are already as persuasive as humans. However, we
know very little about how they do it. This paper investigates the persuasion
strategies of LLMs, comparing them with human-generated arguments. Using a
dataset of 1,251 participants in an experiment, we analyze the persuasion
strategies of LLM-generated and human-generated arguments using measures of
cognitive effort (l
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