SOURCE-LINKED INTELLIGENCE
MUSE: A Theory-Harnessed Story Engine for Vibe Narrativizing
LLMs have been able to generate fluent prose, but high-quality stories also require coordinated decisions about plot, character, and language across planning, drafting, and revision. We formulate Vibe Narrativizing as turning natural-language writing requirements into a finished story. MUSE, a Theory-Harnessed Story Engine, addresses two bottlenecks: rule quality and sustained rule realization. Story theory supplies the rules, and a practical agent harness puts them to work. Knowledge engineering organizes Robert McKee's theory through rule atomization, semantic consolidation, mechanism abstra
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-14T08:09:44.000Z
First collected: 2026-09-20T11:41:07.830Z. This is not the publication date.