From Words To Worlds: Transforming One-line Prompt Into Immersive Multi-modal Digital Stories With Communicative LLM Agent

Sohn Samuel S., Li Danrui, Zhang Sen, Chang Che-jui, Kapadia Mubbasir. Arxiv 2024

[Paper]    
Agentic Prompting Reinforcement Learning Tools

Digital storytelling, essential in entertainment, education, and marketing, faces challenges in production scalability and flexibility. The StoryAgent framework, introduced in this paper, utilizes Large Language Models and generative tools to automate and refine digital storytelling. Employing a top-down story drafting and bottom-up asset generation approach, StoryAgent tackles key issues such as manual intervention, interactive scene orchestration, and narrative consistency. This framework enables efficient production of interactive and consistent narratives across multiple modalities, democratizing content creation and enhancing engagement. Our results demonstrate the framework’s capability to produce coherent digital stories without reference videos, marking a significant advancement in automated digital storytelling.

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