SOURCE-LINKED INTELLIGENCE
The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation
Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate stories, they iteratively edit their prompts to explore narrative possibilities, adjusting characters, redirecting plots, and swapping fictional universes. As aggregated data, these prompts represent rich traces of creative preference at scale. Yet story generation evaluation benchmarks rely on static, one-shot prompts that cannot capture this exploratory behavior. In this work, we study how users revise consecutive story prompts in the wild. Using a
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-13T17:21:22.000Z
First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.