PAUSE: Editable Strategy Artifacts for Long-Form Cultural Story Adaptation

Generative AI systems currently mediate cultural adaptation with hidden decision-making processes. A new intervention, PAUSE (Pause-And-Update Strategy Editing), proposes exposing and allowing human editing of adaptation strategies as structured artifacts. This approach enables greater human control over cultural decisions in long-form story adaptation, with initial tests showing human judges consistently preferring outputs generated with edited strategies over control versions.

Why it matters

This research addresses a critical limitation in generative AI for cultural adaptation, moving towards more transparent and controllable AI-driven creative processes. The ability to inspect and edit AI's strategic decisions offers a pathway for organizations to maintain brand integrity, cultural sensitivity, and creative direction in content generation, which is crucial for global market engagement and avoiding potential misinterpretations or controversies.

Key insights

• Generative AI systems for cultural adaptation often embed cultural decisions within prompts, transient model plans, or final prose, limiting human oversight.
• PAUSE introduces editable 'strategy artifacts' that serve as human control surfaces for cultural decisions in long-form story adaptation.
• These strategy artifacts are structured, allowing for inspection, editing, and projection into downstream stages like character, entity, and chapter localization.
• Experimental results from adapting two Chinese-source serialized novels demonstrated that human edits to these strategies successfully propagated into chapter-level prose.
• In 9 out of 9 comparisons, human judges preferred the output generated using the edited strategies over the control output, indicating improved cultural alignment or quality through human intervention.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2608.28633