World-State Transformations for Neuro-symbolic Interactive Storytelling
Summary
This paper explores using LLMs to predict state changes within rule-based interactive storytelling systems, aiming to improve coherence and player expression. Experiments with Llama 3 70B and Gemini 1.5 Flash show that world-state transformations can maintain consistency while encouraging creative player input.
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# World-State Transformations for Neuro-symbolic Interactive Storytelling Source: [https://arxiv.org/abs/2605.24719](https://arxiv.org/abs/2605.24719) [View PDF](https://arxiv.org/pdf/2605.24719) > Abstract:Large Language Models \(LLMs\) have changed the possibilities of Interactive Storytelling systems that process free\-text user input\. However, as more of these systems are built, evidence continues to mount regarding the story coherence problems that arise when relying solely on them\. Recent research suggests that LLMs can effectively predict state changes within rule\-based Interactive Storytelling systems, triggering pre\-programmed world\-state transformations\. In this paper, we conduct an exploratory evaluation of whether such transformations can serve as a catalyst for player expression while aiming to address the incoherence issues typical of purely LLM\-based approaches\. Building upon a neuro\-symbolic architecture, we conducted experiments using an open\-source model \(Llama 3 70B\) and a closed\-source model \(Gemini 1\.5 Flash\), with testing conducted in both English and Spanish\. Eight participants played two scenarios, carefully designed to assess different evaluation objectives\. Our observations suggest that transformations offer a way to maintain world\-state consistency while encouraging players to interact creatively through their written inputs\. ## Submission history From: Santiago Góngora \[[view email](https://arxiv.org/show-email/3b65268f/2605.24719)\] **\[v1\]**Sat, 23 May 2026 20:14:39 UTC \(2,758 KB\)
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