ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program

2026-07-17 · Source: cs.CV updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Gaming & Interactive Media, Robotics & Autonomous Systems · Depth: Expert, extended

Summary

ETPDesigner is a novel multi-agent framework that automates the generation of interactive, multimodal Electronic Theater Programs (ETPs) directly from raw dramatic scripts. Addressing the limitations of existing text-to-image models in handling long-context narratives and maintaining visual consistency across multi-page designs, ETPDesigner orchestrates specialized agents for semantic script analysis, core poster synthesis, functional background generation, and character asset composition. A central global style anchor mechanism ensures strict aesthetic uniformity across all generated components. The system further enhances ETPs by integrating portrait animation, customized speech synthesis, and persona-grounded Large Language Models, enabling real-time, voice-enabled conversations with virtual characters. To benchmark this task, the ETP-Pro dataset was created, comprising 100 professional theater programs. Evaluations demonstrate ETPDesigner's superior performance in semantic fidelity, aesthetic consistency, and interactivity compared to baselines like Seedream 4.5 and AutoGen.

Key takeaway

For AI Engineers developing narrative-driven multimodal content generation systems, you should consider adopting a multi-agent orchestration framework like ETPDesigner. Its approach of decoupling complex tasks, employing a global style anchor, and using VLM-driven self-refinement is crucial for achieving aesthetic consistency and semantic fidelity across diverse assets. This method enables the creation of interactive experiences, moving beyond static outputs and addressing the limitations of general text-to-image models for long-context, multi-page designs.

Key insights

Multi-agent orchestration enables consistent, interactive multimodal content generation from complex dramatic scripts.

Principles

• Decompose complex generation via specialized agents.
• Anchor global style for cross-asset consistency.
• Use VLM-as-a-Judge for iterative visual optimization.

Method

A six-agent framework processes scripts, synthesizes a style-anchoring poster via RAG-enhanced Tree of Thoughts, generates consistent backgrounds, and programmatically composes assets for ETPs.

In practice

• Automate multi-page theatrical program design.
• Create interactive, conversational virtual characters.
• Ensure aesthetic unity across diverse visual assets.

Topics

• Multi-Agent Systems
• Electronic Theater Programs
• Multimodal Generation
• Stylistic Consistency
• VLM-as-a-Judge
• ETP-Pro Dataset

Code references

• black-forest-labs/flux

Best for: Research Scientist, AI Scientist, Machine Learning Engineer, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.CV updates on arXiv.org.