Drama Llama: An LLM-Powered Storylets Framework for Authorable Responsiveness in Interactive Narrative
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916567545020416 |
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| author | Sun, Yuqian Wang, Phoebe J. Chung, John Joon Young Roemmele, Melissa Kim, Taewook Kreminski, Max |
| author_facet | Sun, Yuqian Wang, Phoebe J. Chung, John Joon Young Roemmele, Melissa Kim, Taewook Kreminski, Max |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_09099 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Drama Llama: An LLM-Powered Storylets Framework for Authorable Responsiveness in Interactive Narrative Sun, Yuqian Wang, Phoebe J. Chung, John Joon Young Roemmele, Melissa Kim, Taewook Kreminski, Max Human-Computer Interaction 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. |
| title | Drama Llama: An LLM-Powered Storylets Framework for Authorable Responsiveness in Interactive Narrative |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2501.09099 |