# Design Techniques for LLM-Powered Interactive Storytelling: A Case Study of the Dramamancer System

arXiv: https://arxiv.org/abs/2601.18785 · HTML: https://mlsanity.com/paper/2601.18785/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 7 references that are in the map.
- First posted on arXiv 26 Jan 2026.

## Builds on (most cited first, 4 of 4)

- [Agents' Room: Narrative Generation through Multi-step Collaboration](https://mlsanity.com/paper/2410.02603/) (2024)
- [Creating Suspenseful Stories: Iterative Planning with Large Language Models](https://mlsanity.com/paper/2402.17119/) (2024)
- [WhatELSE: Shaping Narrative Spaces at Configurable Level of Abstraction for AI-bridged Interactive Storytelling](https://mlsanity.com/paper/2502.18641/) (2025)
- [Drama Llama: An LLM-Powered Storylets Framework for Authorable Responsiveness in Interactive Narrative](https://mlsanity.com/paper/2501.09099/) (2025)

## Abstract (arXiv)

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.