Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866918306059911168 |
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| author | Wang, Tiffany Sun, Yuqian Wang, Yi Roemmele, Melissa Chung, John Joon Young Kreminski, Max |
| author_facet | Wang, Tiffany Sun, Yuqian Wang, Yi Roemmele, Melissa Chung, John Joon Young Kreminski, Max |
| contents | The rise of Large Language Models (LLMs) has enabled a new paradigm for bridging authorial intent and player agency in interactive narrative. We consider this paradigm through the example of Dramamancer, a system that uses an LLM to transform author-created story schemas into player-driven playthroughs. This extended abstract outlines some design techniques and evaluation considerations associated with this system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_18785 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System Wang, Tiffany Sun, Yuqian Wang, Yi Roemmele, Melissa Chung, John Joon Young Kreminski, Max Human-Computer Interaction Artificial Intelligence Computation and Language The rise of Large Language Models (LLMs) has enabled a new paradigm for bridging authorial intent and player agency in interactive narrative. We consider this paradigm through the example of Dramamancer, a system that uses an LLM to transform author-created story schemas into player-driven playthroughs. This extended abstract outlines some design techniques and evaluation considerations associated with this system. |
| title | Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2601.18785 |