Drama Llama: An LLM-Powered Storylets Framework for Authorable
Responsiveness in Interactive Narrative
Max Kreminski Melissa Roemmele Phoebe J. Wang Yuqian Sun John Joon Young Chung Taewook Kim
作者信息
Abstract
In this paper, we present Drama Llama, an LLM-powered storylets framework
that supports the authoring of responsive, open-ended interactive stories. DL
combines the structural benefits of storylet-based systems with the generative
capabilities of large language models, enabling authors to create responsive
interactive narratives while maintaining narrative control. Rather than
crafting complex logical preconditions in a general-purpose or domain-specific
programming language, authors define triggers in natural language that fire at
appropriate moments in the story. Through a preliminary authoring study with
six content authors, we present initial evidence that DL can generate coherent
and meaningful narratives with believable character interactions. This work
suggests directions for hybrid approaches that enhance authorial control while
supporting emergent narrative generation through LLMs.引用本文复制引用
Max Kreminski,Melissa Roemmele,Phoebe J. Wang,Yuqian Sun,John Joon Young Chung,Taewook Kim.Drama Llama: An LLM-Powered Storylets Framework for Authorable
Responsiveness in Interactive Narrative[EB/OL].(2025-01-15)[2026-01-19].https://arxiv.org/abs/2501.09099.学科分类
计算技术、计算机技术
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