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.
@article{arxiv.2601.18785,
title = {Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System},
author = {Tiffany Wang and Yuqian Sun and Yi Wang and Melissa Roemmele and John Joon Young Chung and Max Kreminski},
journal= {arXiv preprint arXiv:2601.18785},
year = {2026}
}
Comments
Extended abstract presented at the 2025 Wordplay Workshop at EMNLP