CASPER in the Machine: Insights into Character Variety in LLM-Generated Stories

Abstract:As LLM-generated text is increasingly used, especially in fictional domains, we explore how much LLM-generated stories differ from human-written stories. In this work, we focus on characters. We borrow definitions from narratology to analyze eight intricate dimensions of character, such as stylization and wholeness. These dimensions consider more than just basic characteristics. They assess how characters are portrayed within their stories. After automatically inferring categories of characters within both LLM and human-written stories, we compare and contrast these two sets of stories. We consider the following overarching questions: (1) Do LLMs and human-written stories have similar characters? and (2) Do LLMs generate stories with a variety of characters? Our analysis includes research questions that focus on stories generated by popular LLMs and recently published human-written stories. We describe a number of interesting similarities, differences and key takeaways.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2606.22454 [cs.CL]

(or arXiv:2606.22454v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2606.22454 Focus to learn more arXiv-issued DOI via DataCite

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