AI 中文总结
研究针对创意人工智能从单步到多模态创作转变中现有系统不足的问题，引入JarvisHub框架，以可编辑画布为核心，通过三层架构让智能体实现持续、人工可控的创意自动化创作。
AI 中文摘要
创意人工智能正从单步资产生成迈向长期多模态创作。尽管近期生成模型能合成高质量图像、视频等创意资产，但现实世界的创意工作需要更多。现有基于提示、聊天和节点的生成系统仅部分支持这种创作状态。近期商业系统虽向智能体辅助创作生产转变，但其封闭架构不利于研究。为此引入JarvisHub，它将可编辑画布作为用户工作区、智能体外部内存等，通过三层架构使智能体在可检查和编辑的创意状态中行动，推动创意智能体从孤立工具使用走向持续、人工可控的创意自动化。
英文摘要
Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high-quality images, videos, audio clips, UI elements, storyboards, slides, and other creative assets, real-world creative work requires more than isolated prompt-output interactions. It involves references, drafts, alternatives, edits, failed attempts, version relations, tool actions, evaluation signals, and human feedback, which together form an evolving project state. Existing prompt-based, chat-based, and node-based generation systems only partially support this state, as they often discard intermediate context, rely on linear conversations, or require manually specified workflows. Recent commercial systems indicate a shift toward agent-assisted creative production, but their closed architectures make it difficult to study how agents represent context, choose tools, revise artifacts, recover from failures, and maintain consistency over time. To address this gap, we introduce JarvisHub, a canvas-native creative agent harness for long-horizon multimodal creation. JarvisHub treats an editable canvas as the user workspace, the agent's external memory, action space, and shared project state, representing multimodal artifacts, dependencies, versions, and feedback as typed canvas nodes and links. Through a three-layer architecture of canvas state, protocol bridge, and agent runtime, JarvisHub enables agents to act within an inspectable and editable creative state. This design moves creative agents beyond isolated tool use toward sustained, human-steerable creative automation, where agents can progressively plan, generate, revise, and organize multimodal projects while users remain able to inspect, guide, and intervene throughout the process.
Comments15 pages, 9 figures. Project page: https://www.jarvishub.site/ Code github: https://github.com/LYL1015/JarvisHub
