The proliferation of generative AI has transformed creative workflows, yet current systems face critical challenges in controllability and content protection. We propose a novel multi-agent framework that addresses both limitations through specialized agent roles and integrated watermarking mechanisms. Unlike existing multi-agent systems focused solely on generation quality, our approach uniquely combines controllable content synthesis with provenance protection during the generation process itself. The framework orchestrates Director/Planner, Generator, Reviewer, Integration, and Protection agents with human-in-the-loop feedback to ensure alignment with user intent while embedding imperceptible digital watermarks. We formalize the pipeline as a joint optimization objective unifying controllability, semantic alignment, and protection robustness. This work contributes to responsible generative AI by positioning multi-agent architectures as a solution for trustworthy creative workflows with built-in ownership tracking and content traceability.

翻译：生成式AI的普及已彻底改变了创意工作流程，然而现有系统在可控性和内容保护方面仍面临严峻挑战。本文提出一种新颖的多智能体框架，通过专门的智能体角色与集成水印机制同时解决这两大局限。与现有仅关注生成质量的多智能体系统不同，我们的方法创新性地将可控内容合成与生成过程中的溯源保护相结合。该框架通过编排导演/规划器、生成器、评审器、集成器与保护器五大智能体，并引入人机协同反馈机制，在确保用户意图对齐的同时嵌入不可感知的数字水印。我们将该流程形式化为统一可控性、语义对齐与保护鲁棒性的联合优化目标。本研究通过将多智能体架构定位为具有内置所有权追踪与内容溯源性可信创意工作流的解决方案，为负责任生成式AI的发展做出贡献。