让用户在画布上手写手绘，与大模型实时互动生成墨迹式回应。
Thinkink: 2D Spatial Ink-native Interaction with LLMs
- 手写或绘画输入，大模型输出以墨迹形式融入共享画布。
- 通过语义树解析墨迹，用轻量界面实现状态化控制。
- 适合创意构思者，支持人机协同的自然交互设计。
人们常通过手写笔记和草图外化想法用于构思。为将大语言模型（LLMs）融入此过程，我们提出Thinkink。用户可输入手写文字或草图，大模型生成的回答以类似墨迹的文字和草图形式，空间化整合至共享画布中。通过语义树流优化墨迹理解，并采用轻量级界面结合状态机实现显式控制。工具设计基于三阶段流程：先通过定性研究（N=12）分析传统与数字书写实践；再通过诊断研究（N=6）识别可用性及人-模型交互挑战；最终通过验证研究（N=10）考察用户如何将Thinkink融入构思过程。本文贡献了面向墨迹原生交互的设计启示与可运行工具，实现用户与大模型在二维画布上的共同书写与绘图。
原文摘要 · Abstract (English)
People often use handwritten notes and sketches to externalize ideas for ideation. To integrate large language models (LLMs) into this practice, we propose Thinkink. Prompts can be handwritten text or drawn sketches with LLM-generated responses visualized as ink-like text and sketches spatially integrated into a shared canvas. A semantic tree streamlines ink interpretation, and a lightweight UI provides explicit control using a state machine. The tool was designed using a three-stage process. A formative study (N=12) examined current practices with conventional and digital inking methods. The results informed a technical probe for a diagnostic study (N=6) identifying usability and human-LLM interaction challenges. This motivated the design of Thinkink, with a final study (N=10) examining how people incorporate it into their ideation practices. We contribute design implications and a tool for ink-native LLM interaction where the user and LLM write and draw in a shared 2D canvas.
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