{"slug": "dramaagent-agentic-storytelling-video-generation", "title": "DramaAgent: Agentic Storytelling Video Generation", "summary": "Researchers released DramaAgent, a hierarchical, agentic, model-agnostic framework for long-form text-to-video-and-audio generation, detailed in arXiv paper 2610.00097v1. DramaAgent adds an upper-level control layer that decomposes generation into story planning, persistent character conditioning, scene-wise synthesis, and reflection-guided targeted repair, maintaining reusable story and character states across scenes and repairing clips affected by identity drift, missing scene semantics, temporal discontinuity, and cross-modal mismatch. Experiments across multiple video generation backbones show DramaAgent improves long-horizon coherence, character consistency, narrative fidelity, and scene-level audio-visual consistency over direct generation and strong baselines, with code at github.com/AIGeeksGroup/DramaAgent.", "body_md": "arXiv:2610.00097v1 Announce Type: new \nAbstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with consistent characters and aligned audio remains challenging. Existing methods often suffer from narrative drift, unstable character identity, weak cross-scene continuity, and audio-visual mismatch over extended sequences. We propose DramaAgent, a hierarchical, agentic, and model-agnostic framework for long-form text-to-video-and-audio generation. Rather than improving the underlying video backbone itself, DramaAgent introduces an upper-level control layer that decomposes generation into story planning, persistent character conditioning, scene-wise synthesis, and reflection-guided targeted repair. The framework maintains reusable story and character states across scenes, diagnoses failures such as identity drift, missing scene semantics, temporal discontinuity, and cross-modal mismatch, and repairs problematic clips in a stage-specific manner. Experiments across multiple video generation backbones show that DramaAgent improves long-horizon coherence, character consistency, narrative fidelity, and scene-level audio-visual consistency over direct generation and strong baselines. These results suggest that hierarchical agentic control is a practical direction for controllable long-form audiovisual generation. Code: https://github.com/AIGeeksGroup/DramaAgent. Website: https://aigeeksgroup.github.io/DramaAgent.", "url": "https://wpnews.pro/news/dramaagent-agentic-storytelling-video-generation", "canonical_source": "https://arxiv.org/abs/2610.00097", "published_at": "2026-10-02 04:00:00+00:00", "updated_at": "2026-10-02 04:17:39.492879+00:00", "lang": "en", "topics": ["artificial-intelligence", "generative-ai", "ai-agents", "ai-research"], "entities": ["DramaAgent", "arXiv", "AIGeeksGroup"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/dramaagent-agentic-storytelling-video-generation", "markdown": "https://wpnews.pro/news/dramaagent-agentic-storytelling-video-generation.md", "text": "https://wpnews.pro/news/dramaagent-agentic-storytelling-video-generation.txt", "jsonld": "https://wpnews.pro/news/dramaagent-agentic-storytelling-video-generation.jsonld"}}