SceneWeave: Audience-Guided Scene Exploration for Dramatic Adaptation

Abstract:Adapting prose into a script requires transforming narration and inner experience into scenes that convey relationships and psychological contradictions. Planning specifies intended effects but leaves their realization in dialogue and action unresolved. Drawing on screenwriters' accounts of revising scenes and their connections to the surrounding work, we present SceneWeave, which uses alternative scene drafts to revise the adaptation as a whole. It writes contrasting treatments of a focal scene, compares the interactions they create, and revises characterization, preceding preparation, subsequent development, and scene order before generating the complete script. The central contribution is to use actual scene writing to inform adaptation decisions and propagate their consequences across the work. We also develop a task-specific writing model and a human-preference model for comparing script drafts. The writing model learns from adaptation examples and human preferences; the preference model combines human and synthetic supervision. Blind reader comparisons favor SceneWeave over a baseline workflow and description-based controls, while content assessment indicates reduced narrative redundancy and strong psychological treatment.

Computation and Language (cs.CL)

arXiv:2610.21737 [cs.CL]

(or arXiv:2610.21737v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.21737 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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