NarrativeSteward: Coordinating Delegation, Guidance, and Verification in Agent-Assisted Interactive Narrative Authoring
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Abstract (arXiv)
Autonomous AI agents can turn authors' goals into interactive narratives by independently organizing and carrying out generation and revision. As agents generate and revise extensive content, authors struggle to grasp its overall structure, local details, and relationships, complicating continued guidance. We present NarrativeSteward, an authoring environment that organizes outlines, worldbuilding, and narrative graphs as linked artifacts for agent implementation and author guidance. Agent dialogue and project-wide structural review help authors understand the evolving work and guide local and cross-layer revisions, while change records and execution verification help authors assess the resulting work. Technical tests validated the system's change records, recovery mechanisms, and execution diagnostics. In a 12-participant within-subject study, NarrativeSteward supported easier formulation of revision requests and inspection of changes, and greater perceived understanding of changes and story structure, than general-purpose agents. Qualitative findings show how reviewing the work and feedback helps authors develop requirements and guide subsequent delegation. We open-source NarrativeSteward at https://github.com/Tencent/NarrativeSteward.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 22 of its 73 references that are in the map. First posted on arXiv 30 Sep 2026.
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References · 22
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
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- 2025Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systemscited by 7
- 2026Developer Interaction Patterns with Proactive AI: A Five-Day Field Studycited by 7
- 2025Partnering with Generative AI: Experimental Evaluation of Human-Led and Model-Led Interaction in Human-AI Co-Creationcited by 4
- 2024Boosting Mixed-Initiative Co-Creativity in Game Design: A Tutorialcited by 3
- 2026How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of Screenwriterscited by 3
- 2025DiaryPlay: AI-Assisted Authoring of Interactive Vignettes for Everyday Storytellingcited by 2
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