发表机构
National Taiwan University; MoonShine Animation Studio; Cornell Tech; UCLA（国立台湾大学; 月光动画工作室; 康奈尔理工学院; 加州大学洛杉矶分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
MOONWALK提出意图-证据-行动对齐框架，通过结构化评审系统增强动画前期制作中初级-主管协作的意图对齐、决策可追溯性和清单可执行性，并验证其优于聊天机器人界面。
AI 中文摘要
动画和视觉特效前期制作评审要求团队将松散指定的创意意图——简报、不断演变的规格、异构参考以及口头决策——转化为初级艺术家无需反复澄清即可执行的修订。在实践中，标准在迭代中漂移，评审判断失去其证据基础，请求背后的推理很少能在高级与初级交接中幸存。我们提出了一个意图-证据-行动对齐的设计框架：意图被明确表达为共享项目记录，判断锚定于有根据的证据，授权决策被转化为直接关联参考注释的清晰修订任务。我们将该框架实例化为MOONWALK，一个专业的制作前期评审系统，包含共享意图记录、参考/规格锚定、结构化进行中工作比较以及主管授权的行动规划。在此工作流中，AI处理行政协调——标记缺失上下文和组织注释——而艺术家保留完全的创意方向。一项与专业从业者进行的内部工作室研究，使用匹配的制作材料将MOONWALK与仅聊天（聊天机器人）界面进行比较，同时参与者的现有工作流提供回顾性生态基线。结果表明，意图对齐、决策可追溯性和清单可执行性更强，同时也表明审美权威和最终优先级必须保留给从业者。该评估确立了集成结构化工作流相对于非结构化对话式AI聊天机器人的价值。代码：此https URL
英文摘要
Animation and VFX pre-production review requires teams to translate loosely specified creative intent--briefs, evolving specifications, heterogeneous references, and verbal decisions--into revisions that junior artists can execute without repeated clarification. In practice, criteria drift across iterations, review judgments lose their evidential basis, and the reasoning behind a request rarely survives the senior-junior handoff. We contribute a design framework for intent-evidence-action alignment: intent is articulated into a shared project record, judgments are anchored to grounded evidence, and authorized decisions are converted into clear revision tasks tied directly to reference notes. We instantiate this framework in MOONWALK, a professional pre-production review system comprising a shared intent record, reference/specification anchoring, structured work-in-progress comparison, and supervisor-authorized action planning. In this workflow, AI handles administrative coordination--flagging missing context and organizing notes--while artists retain full creative direction. An in-studio study with professional practitioners compares MOONWALK with a chat-only (chatbot) interface using matched production materials, while participants' existing workflows provide a retrospective ecological baseline. Results indicate stronger intent alignment, decision traceability, and checklist executability, while also showing that aesthetic authority and final prioritization must remain with practitioners. The evaluation establishes the value of the integrated structured workflow over unstructured conversational AI chatbot. Code: https://github.com/Akinesia112/Moonwalk/tree/english-version
