# AniME: Adaptive Multi-Agent Planning for Long Animation Generation

arXiv: https://arxiv.org/abs/2508.18781 · HTML: https://mlsanity.com/paper/2508.18781/

## 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 (most cited first, 6 of 6)

- [Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs](https://mlsanity.com/paper/2401.11708/) (2024)
- [Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization](https://mlsanity.com/paper/2404.09956/) (2024)
- [Automated Movie Generation via Multi-Agent CoT Planning](https://mlsanity.com/paper/2503.07314/) (2025)
- [Anim-Director: A Large Multimodal Model Powered Agent for Controllable Animation Video Generation](https://mlsanity.com/paper/2408.09787/) (2024)
- [VALL-T: Decoder-Only Generative Transducer for Robust and Decoding-Controllable Text-to-Speech](https://mlsanity.com/paper/2401.14321/) (2024)
- [AniSora: Exploring the Frontiers of Animation Video Generation in the Sora Era](https://mlsanity.com/paper/2412.10255/) (2024)

## Built on by (most cited first, 7 of 7)

- [Hollywood Town: Long-Video Generation via Cross-Modal Multi-Agent Orchestration](https://mlsanity.com/paper/2510.22431/) (2025)
- [GroundShot: Visually Consistent Multi-Shot Long Video Generation via Entity-Grounded Shot Scheduling](https://mlsanity.com/paper/2606.20799/) (2026)
- [CogPortrait: Fine-Grained Eye-Region Control in Portrait Animation via Hierarchical Agent Planning](https://mlsanity.com/paper/2605.28056/) (2026)
- [FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling](https://mlsanity.com/paper/2607.19038/) (2026)
- [Self-Reasoning Agentic Framework for Narrative Product Grid-Collage Generation](https://mlsanity.com/paper/2604.16958/) (2026)
- [StateFlow: Building, Evolving, and Accessing 3D World States for Previsualization](https://mlsanity.com/paper/2608.12314/) (2026)
- [Agentic Visual Generation: From Generative Models to Agentic Control](https://mlsanity.com/paper/2609.06758/) (2026)

## 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.