SketchAgent: Generating Structured Diagrams from Hand-Drawn Sketches
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Abstract (arXiv)
Hand-drawn sketches are a natural and efficient medium for capturing and conveying ideas. Despite significant advancements in controllable natural image generation, translating freehand sketches into structured, machine-readable diagrams remains a labor-intensive and predominantly manual task. The primary challenge stems from the inherent ambiguity of sketches, which lack the structural constraints and semantic precision required for automated diagram generation. To address this challenge, we introduce SketchAgent, a multi-agent system designed to automate the transformation of hand-drawn sketches into structured diagrams. SketchAgent integrates sketch recognition, symbolic reasoning, and iterative validation to produce semantically coherent and structurally accurate diagrams, significantly reducing the need for manual effort. To evaluate the effectiveness of our approach, we propose the Sketch2Diagram Benchmark, a comprehensive dataset and evaluation framework encompassing eight diverse diagram categories, such as flowcharts, directed graphs, and model architectures. The dataset comprises over 6,000 high-quality examples with token-level annotations, standardized preprocessing, and rigorous quality control. By streamlining the diagram generation process, SketchAgent holds great promise for applications in design, education, and engineering, while offering a significant step toward bridging the gap between intuitive sketching and machine-readable diagram generation. The benchmark is released at https://huggingface.co/datasets/DiagramAgent/Sketch2Diagram-Benchmark.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 35 of its 47 references that are in the map. First posted on arXiv 2 Aug 2025.
Builds on
35 of 47 references.
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Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026DiagramRAG: A Lightweight Framework to Retrieve Scientific Diagram for Figure Generation27 May 2026
- 2026Deltaynamics: Language-Based Representation for Inferring Rigid-Body Dynamics From Videos20 May 2026
- 2026PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents11 May 2026
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