# MOONWALK: Mediating Operations with Intent-Evidence-Action Alignment Across Junior-Supervisor Review Workflows in Animation/VFX Pre-Production

arXiv: https://arxiv.org/abs/2609.10385 · HTML: https://mlsanity.com/paper/2609.10385/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 32 of its 74 references that are in the map.
- First posted on arXiv 9 Sep 2026.

## Builds on (most cited first, 30 of 32)

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- [More AI Assistance Reduces Cognitive Engagement: Examining the AI Assistance Dilemma in AI-Supported Note-Taking](https://mlsanity.com/paper/2509.03392/) (2025)
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- [Compositional Structures as Substrates for Human-AI Co-creation Environment: A Design Approach and A Case Study](https://mlsanity.com/paper/2503.04103/) (2025)
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- [LADICA: A Large Shared Display Interface for Generative AI Cognitive Assistance in Co-Located Team Collaboration](https://mlsanity.com/paper/2409.13968/) (2024)
- [GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design](https://mlsanity.com/paper/2508.15227/) (2025)
- [Feedback by Design: Understanding and Overcoming User Feedback Barriers in Conversational Agents](https://mlsanity.com/paper/2602.01405/) (2026)
- [PrevizWhiz: Combining Rough 3D Scenes and 2D Video to Guide Generative Video Previsualization](https://mlsanity.com/paper/2602.03838/) (2026)
- [MeetMap: Real-Time Collaborative Dialogue Mapping with LLMs in Online Meetings](https://mlsanity.com/paper/2502.01564/) (2025)
- [MapStory: Prototyping Editable Map Animations with LLM Agents](https://mlsanity.com/paper/2505.21966/) (2025)
- [Reflexis: Supporting Reflexivity and Rigor in Collaborative Qualitative Analysis through Design for Deliberation](https://mlsanity.com/paper/2601.15445/) (2026)
- [Are We On Track? AI-Assisted Active and Passive Goal Reflection During Meetings](https://mlsanity.com/paper/2504.01082/) (2025)

## Abstract (arXiv)

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