AniME: Adaptive Multi-Agent Planning for Long Animation Generation
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Abstract (arXiv)
We present AniME, a director-oriented multi-agent system for automated long-form anime production, covering the full workflow from a story to the final video. The director agent keeps a global memory for the whole workflow, and coordinates several downstream specialized agents. By integrating customized Model Context Protocol (MCP) with downstream model instruction, the specialized agent adaptively selects control conditions for diverse sub-tasks. AniME produces cinematic animation with consistent characters and synchronized audio visual elements, offering a scalable solution for AI-driven anime creation.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 6 of its 8 references that are in the map. First posted on arXiv 26 Aug 2025.
Builds on
6 of 8 references.
References · 6
- 2024Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMscited by 224
- 2024Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimizationcited by 97
- 2025Automated Movie Generation via Multi-Agent CoT Planningcited by 89
- 2024Anim-Director: A Large Multimodal Model Powered Agent for Controllable Animation Video Generationcited by 37
- 2024VALL-T: Decoder-Only Generative Transducer for Robust and Decoding-Controllable Text-to-Speechcited by 23
- 2024AniSora: Exploring the Frontiers of Animation Video Generation in the Sora Eracited by 8
Built on by
Citing papers per year: 2025: 1; 2026: 6.
7 papers.
- 2025Hollywood Town: Long-Video Generation via Cross-Modal Multi-Agent Orchestrationcited by 10
- 2026GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Schedulingcited by 5
- 2026CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planningcited by 2
- 2026FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modelingcited by 2
- 2026Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generationcited by 1
- 2026StateFlow: Building, Evolving, and Accessing 3D World States for Previsualizationcited by 1
- 2026Agentic Visual Generation: From Generative Models to Agentic Controlcited by 1
- 2026Agentic Visual Generation: From Generative Models to Agentic Control6 Sep 2026
- 2026StateFlow: Building, Evolving, and Accessing 3D World States for Previsualization12 Aug 2026
- 2026FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling21 Jul 2026
- 2026GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling18 Jun 2026
- 2026CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning27 May 2026
- 2026Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation18 Apr 2026
- 2025Hollywood Town: Long-Video Generation via Cross-Modal Multi-Agent Orchestration25 Oct 2025
Similar, not cited
Close in wording, no citation either way
- 2026AnimeAgent: Is the Multi-Agent via Image-to-Video models a Good Disney Storytelling Artist?
- 2024AesopAgent: Agent-driven Evolutionary System on Story-to-Video Production
- 2026FRAMEWORKERS: A Dynamic Multi-Agent Framework for AI-Generated Video Production
- 2026Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation
- 2024From Data to Story: Towards Automatic Animated Data Video Creation with LLM-based Multi-Agent Systems
- 2026Cutscene Agent: An LLM Agent Framework for Automated 3D Cutscene Generation
- 2026AniMatrix: An Anime Video Generation Model that Thinks in Art, Not Physics
- 2026MangaFlow: An End-to-End Agentic Framework for Controllable Story to Manga Generation