意图标记：探索支持细粒度人机生成式AI协同创作工作流的微提示交互
Intent Tagging: Exploring Micro-Prompting Interactions for Supporting Granular Human-GenAI Co-Creation Workflows
AI总结：
针对GenAI创作中意图对齐与提示构建难题，提出基于意图标记的IntentTagger系统，支持细粒度微提示交互，用户研究验证其灵活表达意图的价值。
摘要：
尽管生成式AI（GenAI）系统在增强内容创作方面具有潜力，但用户往往难以将GenAI有效整合到其创意工作流中。核心挑战包括：AI生成内容与用户意图的不一致（意图激发与对齐）、用户对于如何最好地向AI系统传达其意图的不确定性（提示构建），以及AI系统在支持多样化创意工作流方面灵活性不足（工作流灵活性）。受这些挑战的驱动，我们创建了IntentTagger：一个基于意图标记（Intent Tags）概念的幻灯片创作系统，意图标记是封装用户意图的小型原子概念单元，用于探索人机GenAI协同创作工作流中的细粒度、非线性微提示交互。我们进行的12名参与者的用户研究，提供了关于在不同模糊度水平下灵活表达意图的价值、元意图激发，以及意图标记驱动工作流的益处与挑战的见解。最后，我们讨论了研究结果的更广泛含义以及GenAI支持的内容创作工作流的设计考量。
英文摘要：
Despite Generative AI (GenAI) systems' potential for enhancing content creation, users often struggle to effectively integrate GenAI into their creative workflows. Core challenges include misalignment of AI-generated content with user intentions (intent elicitation and alignment), user uncertainty around how to best communicate their intents to the AI system (prompt formulation), and insufficient flexibility of AI systems to support diverse creative workflows (workflow flexibility). Motivated by these challenges, we created IntentTagger: a system for slide creation based on the notion of Intent Tags - small, atomic conceptual units that encapsulate user intent - for exploring granular and non-linear micro-prompting interactions for Human-GenAI co-creation workflows. Our user study with 12 participants provides insights into the value of flexibly expressing intent across varying levels of ambiguity, meta-intent elicitation, and the benefits and challenges of intent tag-driven workflows. We conclude by discussing the broader implications of our findings and design considerations for GenAI-supported content creation workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
