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A high-performing teacher is built that makes navigation evidence selection explicit and compressible, and a compact student is trained by transferring both where to attend and what to do, then further match action distributions during fine-tuning.
This work forms image-to-editable reconstruction, which recovers a structured, directly manipulable artifact from a raster image while preserving its visual and semantic content, and introduces DrawAI, comprising an agentic benchmark, DrawAI-Bench, and a reconstruction workflow, DrawAI-Flow.
Vision-language models (VLMs) increasingly rely on point coordinates as a compact and executable interface for visual grounding in GUI interaction, robotic manipulation, and interactive visual systems. However, learning reliable pointing behavior remains difficult because the supervision space is inherently non-unique:...
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