{"id":1013550,"date":"2024-03-08T14:02:51","date_gmt":"2024-03-08T22:02:51","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=1013550"},"modified":"2024-07-03T15:09:22","modified_gmt":"2024-07-03T22:09:22","slug":"geneva-generating-and-visualizing-branching-narratives-using-llms","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/geneva-generating-and-visualizing-branching-narratives-using-llms\/","title":{"rendered":"GENEVA: GENErating and Visualizing branching narratives using LLMs"},"content":{"rendered":"
Dialogue-based Role Playing Games (RPGs) require powerful storytelling. The narratives of these may take years to write and typically involve a large creative team. In this work, we demonstrate the potential of large generative text models to assist this process. \\textbf{GENEVA}, a prototype tool, generates a rich narrative graph with branching and reconverging storylines that match a high-level narrative description and constraints provided by the designer. A large language model (LLM), GPT-4, is used to generate the branching narrative and to render it in a graph format in a two-step process. We illustrate the use of GENEVA in generating new branching narratives for four well-known stories under different contextual constraints. This tool has the potential to assist in game development, simulations, and other applications with game-like properties. Link to the GENEVA tool: Visualizing Generated Narratives (msr-emergence.com) (opens in new tab)<\/span><\/a><\/p>\n <\/p>\n