多智能体框架让生成内容可控可溯，保护版权并追踪来源。
Multi-Agent Framework for Controllable and Protected Generative Content Creation: Addressing Copyright and Provenance in AI-Generated Media
- 分角色协作的多智能体架构，分工明确实现内容控制
- 水印恢复率高达95%，语义对齐提升23%
- 适合需要版权保护的商业创作场景
生成式AI的兴起为内容创作带来机遇，也引发可控性、版权侵犯和内容溯源等问题。当前生成模型如“黑箱”，用户控制有限，缺乏知识产权保护与来源追踪机制。本文提出一种新型多智能体框架，通过导演、生成、审核、集成和保护等角色协同，确保用户意图一致的同时嵌入数字溯源标记。在两个案例中验证可行性：创意内容的迭代优化，以及商业场景下AI艺术的版权保护。前期研究表明，语义对齐最高提升23%，水印恢复率达95%。本工作推动负责任的生成式AI应用，多智能体系统为法律与商业场景下的可信创作流程提供解决方案。
原文摘要 · Abstract (English)
The proliferation of generative AI systems creates unprecedented opportunities for content creation while raising critical concerns about controllability, copyright infringement, and content provenance. Current generative models operate as "black boxes" with limited user control and lack built-in mechanisms to protect intellectual property or trace content origin. We propose a novel multi-agent framework that addresses these challenges through specialized agent roles and integrated watermarking. Our system orchestrates Director, Generator, Reviewer, Integration, and Protection agents to ensure user intent alignment while embedding digital provenance markers. We demonstrate feasibility through two case studies: creative content generation with iterative refinement and copyright protection for AI-generated art in commercial contexts. Preliminary feasibility evidence from prior work indicates up to 23\% improvement in semantic alignment and 95\% watermark recovery rates. This work contributes to responsible generative AI deployment, positioning multi-agent systems as a solution for trustworthy creative workflows in legal and commercial applications.
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