Recent advances in video generation have produced models capable of synthesizing stunning visual content from simple text prompts. However, these models struggle to generate long-form, coherent narratives from high-level concepts like dialogue, revealing a ``semantic gap'' between a creative idea and its cinematic execution. To bridge this gap, we introduce a novel, end-to-end agentic framework for dialogue-to-cinematic-video generation. Central to our framework is ScripterAgent, a model trained to translate coarse dialogue into a fine-grained, executable cinematic script. To enable this, we construct ScriptBench, a new large-scale benchmark with rich multimodal context, annotated via an expert-guided pipeline. The generated script then guides DirectorAgent, which orchestrates state-of-the-art video models using a cross-scene continuous generation strategy to ensure long-horizon coherence. Our comprehensive evaluation, featuring an AI-powered CriticAgent and a new Visual-Script Alignment (VSA) metric, shows our framework significantly improves script faithfulness and temporal fidelity across all tested video models. Furthermore, our analysis uncovers a crucial trade-off in current SOTA models between visual spectacle and strict script adherence, providing valuable insights for the future of automated filmmaking.
@article{arxiv.2601.17737,
title = {The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generation},
author = {Chenyu Mu and Xin He and Qu Yang and Wanshun Chen and Jiadi Yao and Huang Liu and Zihao Yi and Bo Zhao and Xingyu Chen and Ruotian Ma and Fanghua Ye and Erkun Yang and Cheng Deng and Zhaopeng Tu and Xiaolong Li and Linus},
journal= {arXiv preprint arXiv:2601.17737},
year = {2026}
}