Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs

This paper presents a novel framework for automated game template generation by transforming Game Design Documents (GDDs) into functional Unity game prototypes using Natural Language Processing (NLP) and multi-modal Large Language Models (LLMs). We introduce an end-to-end system that parses GDDs, extracts structured specifications, and synthesizes Unity-compatible C# code that implements the core mechanics, systems, and architecture defined in the documentation. Evaluation results demonstrate high adherence to GDD specifications across multiple game genres and significant improvements over baseline models.

arXiv Preprint