 | Beyond achieving state-of-the-art (SOTA) performance in standard multilingual document parsing among models of comparable size, dots.mocr excels at converting structured graphics (e.g., charts, UI layouts, scientific figures and etc.) directly into SVG code. Its core capabilities encompass grounding, recognition, semantic understanding, and interactive dialogue. [link] [comments] |
rednote-hilab/dots.mocr · Hugging Face
Reddit r/LocalLLaMA / 3/20/2026
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Key Points
- dots.mocr, released by rednote-hilab on Hugging Face, achieves state-of-the-art multilingual document parsing among similarly sized models.
- It excels at converting structured graphics such as charts, UI layouts, and scientific figures directly into SVG code.
- Its capabilities combine grounding, recognition, semantic understanding, and interactive dialogue to enable end-to-end document understanding.
- The release suggests potential workflows for automated extraction of vector graphics, supporting tasks like data visualization, UI prototyping, and figure digitization.
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