AesopAgent: Agent-driven Evolutionary System on Story-to-Video Production
On the map: LLM agents and tool use → Multimodal and embodied agents
Abstract (arXiv)
The Agent and AIGC (Artificial Intelligence Generated Content) technologies have recently made significant progress. We propose AesopAgent, an Agent-driven Evolutionary System on Story-to-Video Production. AesopAgent is a practical application of agent technology for multimodal content generation. The system integrates multiple generative capabilities within a unified framework, so that individual users can leverage these modules easily. This innovative system would convert user story proposals into scripts, images, and audio, and then integrate these multimodal contents into videos. Additionally, the animating units (e.g., Gen-2 and Sora) could make the videos more infectious. The AesopAgent system could orchestrate task workflow for video generation, ensuring that the generated video is both rich in content and coherent. This system mainly contains two layers, i.e., the Horizontal Layer and the Utility Layer. In the Horizontal Layer, we introduce a novel RAG-based evolutionary system that optimizes the whole video generation workflow and the steps within the workflow. It continuously evolves and iteratively optimizes workflow by accumulating expert experience and professional knowledge, including optimizing the LLM prompts and utilities usage. The Utility Layer provides multiple utilities, leading to consistent image generation that is visually coherent in terms of composition, characters, and style. Meanwhile, it provides audio and special effects, integrating them into expressive and logically arranged videos. Overall, our AesopAgent achieves state-of-the-art performance compared with many previous works in visual storytelling. Our AesopAgent is designed for convenient service for individual users, which is available on the following page: https://aesopai.github.io/.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 57 of its 67 references that are in the map. First posted on arXiv 12 Mar 2024.
Builds on
57 of 67 references.
References · 57
- 2017Attention Is All You Needcited by 59,932
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2023GPT-4 Technical Reportcited by 18,132
- 2023Visual Instruction Tuningcited by 7,792
- 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Modelscited by 6,069
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2017Neural Discrete Representation Learningcited by 4,650
- 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
38 more
- 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
- 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
- 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,765
- 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,761
- 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
- 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
- 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
- 2016Generative Adversarial Text to Image Synthesiscited by 735
- 2023ModelScope Text-to-Video Technical Reportcited by 651
- 2023ViperGPT: Visual Inference via Python Execution for Reasoningcited by 591
- 2023Structure and Content-Guided Video Synthesis with Diffusion Modelscited by 589
- 2017MoCoGAN: Decomposing Motion and Content for Video Generationcited by 523
- 2023MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Actioncited by 511
- 2023Simple and Controllable Music Generationcited by 480
- 2022Phenaki: Variable Length Video Generation From Open Domain Textual Descriptioncited by 475
- 2023MusicLM: Generating Music From Textcited by 442
- 2016Generating Videos with Scene Dynamicscited by 376
- 2023Making Retrieval-Augmented Language Models Robust to Irrelevant Contextcited by 364
- 2022CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformerscited by 305
- 2023Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memorycited by 288
- 2023LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generationcited by 258
- 2023Auto-GPT for Online Decision Making: Benchmarks and Additional Opinionscited by 250
- 2018Music Transformercited by 207
- 2023Recommender Systems with Generative Retrievalcited by 191
- 2023Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Modelscited by 180
- 2023NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generationcited by 170
- 2017Video Generation From Textcited by 153
- 2018StoryGAN: A Sequential Conditional GAN for Story Visualizationcited by 137
- 2023ChatDB: Augmenting LLMs with Databases as Their Symbolic Memorycited by 136
- 2023NExT-Chat: An LMM for Chat, Detection and Segmentationcited by 79
- 2023Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-Incited by 71
- 2024Vlogger: Make Your Dream A Vlogcited by 70
- 2023RET-LLM: Towards a General Read-Write Memory for Large Language Modelscited by 64
- 2023A Multi-Task Embedder For Retrieval Augmented LLMscited by 63
- 2024VideoStudio: Generating Consistent-Content and Multi-Scene Videoscited by 62
- 2020XGPT: Cross-modal Generative Pre-Training for Image Captioningcited by 51
50 most cited of 57 All 57 (JSON)
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Citing papers per year: 2024: 5; 2025: 3; 2026: 4.
12 papers.
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- 2024StoryAgent: Customized Storytelling Video Generation via Multi-Agent Collaborationcited by 28
- 2025MAViS: A Multi-Agent Framework for Long-Sequence Video Storytellingcited by 19
- 2024CinePreGen: Camera Controllable Video Previsualization via Engine-powered Diffusioncited by 7
- 2024Aligning Audio-Visual Joint Representations with an Agentic Workflowcited by 4
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applicationscited by 3
- 2025ViStoryBench: Comprehensive Benchmark Suite for Story Visualizationcited by 2
- 2026Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generationcited by 2
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- 2026Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation7 Sep 2026
- 2026FRAMEWORKERS: A Dynamic Multi-Agent Framework for AI-Generated Video Production30 Aug 2026
- 2026CineForge: Self-Improving Agents for Long-Horizon Video Generation30 Aug 2026
- 2025MAViS: A Multi-Agent Framework for Long-Sequence Video Storytelling11 Aug 2025
- 2025ViStoryBench: Comprehensive Benchmark Suite for Story Visualization30 May 2025
- 2025From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review28 Apr 2025
- 2024StoryAgent: Customized Storytelling Video Generation via Multi-Agent Collaboration7 Nov 2024
- 2024Aligning Audio-Visual Joint Representations with an Agentic Workflow30 Oct 2024
- 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applications28 Oct 2024
- 2024CinePreGen: Camera Controllable Video Previsualization via Engine-powered Diffusion30 Aug 2024
- 2024A Survey on Self-Evolution of Large Language Models22 Apr 2024
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