MUSE: מנוע סיפורים שמשתמש בתאוריות ליצירת סיפורים

תקציר מקורי באנגליתarXiv:2609.15188v1 Announce Type: new Abstract: LLMs can generate fluent prose. Story quality depends on how decisions about plot, character, and language work together across planning, drafting, and revision. Guiding these decisions presents two bottlenecks: the quality of story guidance and its sustained use. We formulate Vibe Narrativizing as the task of turning natural-language writing requirements into a finished story and present MUSE, a Theory-Harnessed Story Engine. MUSE organizes story knowledge as guidance for specific decisions and carries those decisions into subsequent creative work. Knowledge engineering develops Robert McKee's story theory through rule atomization, semantic consolidation, and mechanism abstraction; a single source of truth and layered disclosure organize the