mlsanityData to 7 Oct 2026

Co-Director: Agentic Generative Video Storytelling

arXiv 2604.24842 ↗First posted 27 Apr 2026cs.AI cs.MA cs.MMcited by 2

On the map: Diffusion models → Video generation

also in 1 more
Abstract (arXiv)

While diffusion models generate high-fidelity video clips, transforming them into coherent storytelling engines remains challenging. Current agentic pipelines automate this via chained modules but suffer from semantic drift and cascading failures due to independent, handcrafted prompting. We present Co-Director, a hierarchical multi-agent framework formalizing video storytelling as a global optimization problem. To ensure semantic coherence, we introduce hierarchical parameterization: a multi-armed bandit globally identifies promising creative directions, while a local multimodal self-refinement loop mitigates identity drift and ensures sequence-level consistency. This balances the exploration of novel narrative strategies with the exploitation of effective creative configurations. For evaluation, we introduce GenAD-Bench, a 400-scenario dataset of fictional products for personalized advertising. Experiments demonstrate that Co-Director significantly outperforms state-of-the-art baselines, offering a principled approach that seamlessly generalizes to broader cinematic narratives. Project Page: https://co-director-agent.github.io/

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Video generation, one of 14 directions in Diffusion models. Builds on 15 of its 51 references that are in the map. First posted on arXiv 27 Apr 2026.

Builds on

15 of 51 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024LTX-Video: Realtime Video Latent Diffusion30 Dec
  2. 2024MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequence23 Jul

Other references · 13

  1. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,536
  2. 2024Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameterscited by 1,928
  3. 2024TextGrad: Automatic "Differentiation" via Textcited by 250
  4. 2023VideoDirectorGPT: Consistent Multi-scene Video Generation via LLM-Guided Planningcited by 138
  5. 2025Mixture of Contexts for Long Video Generationcited by 90
  6. 2025Automated Movie Generation via Multi-Agent CoT Planningcited by 82
  7. 2025Feedback Descent: Open-Ended Text Optimization via Pairwise Comparisoncited by 42
  8. 2025FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generationcited by 28
  9. 2025Hollywood Town: Long-Video Generation via Cross-Modal Multi-Agent Orchestrationcited by 10
  10. 2026The Script is All You Need: An Agentic Framework for Long-Horizon Dialogue-to-Cinematic Video Generationcited by 8
  11. 2025AutoMV: An Automatic Multi-Agent System for Music Video Generationcited by 7
  12. 2025PersonaVlog: Personalized Multimodal Vlog Generation with Multi-Agent Collaboration and Iterative Self-Correctioncited by 4
1 more
  1. 2025ViStoryBench: Comprehensive Benchmark Suite for Story Visualizationcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation
  2. 2026ViMax: Agentic Video Generation
  3. 2026StoryEngine: A State-Grounded Agentic Framework for Video Storytelling
  4. 2024From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems
  5. 2025Prompt-Driven Agentic Video Editing System: Autonomous Comprehension of Long-Form, Story-Driven Media
  6. 2026CineForge: Self-Improving Agents for Long-Horizon Video Generation
  7. 2026Bridging Creative Intent and Visual Quality: Creator-Driven Recurrent Video Generation with Agentic Feedback Loops
  8. 2026AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist?