From Words to Worlds: Transforming One-line Prompt into Immersive Multi-modal Digital Stories with Communicative LLM Agent
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 15 of its 48 references that are in the map. First posted on arXiv 15 Jun 2024.
Builds on
15 of 48 references.
References · 15
- 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
- 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,418
- 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
- 2023Large Language Modelscited by 774
- 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
- 2023Synthesizing Physical Character-Scene Interactionscited by 102
- 2022StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuationcited by 74
- 2019Story Realization: Expanding Plot Events into Sentencescited by 35
- 2022Persona-Guided Planning for Controlling the Protagonist's Persona in Story Generationcited by 15
- 2023AdaptNet: Policy Adaptation for Physics-Based Character Controlcited by 15
- 2023Story-to-Motion: Synthesizing Infinite and Controllable Character Animation from Long Textcited by 15
- 2023The Five-Dollar Model: Generating Game Maps and Sprites from Sentence Embeddingscited by 14
Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2025LLM Agents for Education: Advances and Applicationscited by 59
- 2024The Effects of Embodiment and Personality Expression on Learning in LLM-based Educational Agentscited by 13
- 2025Character-Centered Dialogue Generation from Scene-Level Promptscited by 2
- 2026Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generationcited by 2
- 2026Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation7 Sep 2026
- 2025Character-Centered Dialogue Generation from Scene-Level Prompts22 May 2025
- 2025LLM Agents for Education: Advances and Applications14 Mar 2025
- 2024The Effects of Embodiment and Personality Expression on Learning in LLM-based Educational Agents24 Jun 2024
Similar, not cited
Close in wording, no citation either way
- 2025MM-StoryAgent: Immersive Narrated Storybook Video Generation with a Multi-Agent Paradigm across Text, Image and Audio
- 2024DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts
- 2024From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems
- 2025StoryWriter: A Multi-Agent Framework for Long Story Generation
- 2026Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation
- 2024Story3D-Agent: Exploring 3D Storytelling Visualization with Large Language Models
- 2026Improving Collaborative Storytelling with a Multi-Agent Framework Based on Large Language Models
- 2026Co-Director: Agentic Generative Video Storytelling