Do Large Language Models Always Tell The Same Stories?

This study investigates the narrative diversity of outputs generated by ten large language models (LLMs), revealing that LLMs produce more similar stories compared to human-written narratives. Using a contrastive framework and a dataset from r/WritingPrompts, the research highlights that frontier models tend to converge on a generic narrative style, lacking the diversity found in human storytelling. The findings suggest that common strategies like negative prompting and temperature scaling do not effectively enhance output diversity, which is critical for practitioners aiming to create varied and engaging AI-generated content.