Preacher: Paper-to-Video Agentic System
Liu, Jingwei, Yang, Ling, Luo, Hao, Wang, Fan, Li, Hongyan, Wang, Mengdi
–arXiv.org Artificial Intelligence
The paper-to-video task converts a research paper into a structured video abstract, distilling key concepts, methods, and conclusions into an accessible, well-organized format. While state-of-the-art video generation models demonstrate potential, they are constrained by limited context windows, rigid video duration constraints, limited stylistic diversity, and an inability to represent domain-specific knowledge. To address these limitations, we introduce Preacher, the first paper-to-video agentic system. Preacher employs a topdown approach to decompose, summarize, and reformulate the paper, followed by bottom-up video generation, synthesizing diverse video segments into a coherent abstract. To align cross-modal representations, we define key scenes and introduce a Progressive Chain of Thought (P-CoT) for granular, iterative planning. Preacher successfully generates high-quality video abstracts across five research fields, demonstrating expertise beyond current video generation models. Code will be released at: https://github.com/Gen-Verse/Paper2Video
arXiv.org Artificial Intelligence
Sep-9-2025
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- Hubei Province > Wuhan (0.04)
- Zhejiang Province > Hangzhou (0.04)
- Europe > Germany
- Bavaria > Upper Bavaria > Munich (0.04)
- Asia > China
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