aiqbench analysis
Thinkink bridges the gap between analog ideation workflows and modern large language models by enabling direct interaction on a 2D canvas where text and sketches are treated as native inputs rather than digital artifacts. This research advances human-computer interaction within AI by demonstrating how semantic trees can streamline the interpretation of handwritten prompts, offering a practical framework for integrating generative capabilities into natural creative processes without disrupting established note-taking habits.
Thinkink: 2D Spatial Ink-native Interaction with LLMs
arXiv:2607.21468v1 Announce Type: cross Abstract: 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.
Abstract: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.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)
arXiv:2607.21468 [cs.HC]
(or arXiv:2607.21468v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2607.21468 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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