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We introduce SVGenius, the first large-scale complexity-stratified benchmark accessing (M)LLMs capabilities across three progressive dimensions: **Understanding** (perceptua and semantic QA), **Editing** (bug fixing, code optimization, style editing), and **Generation** (text-to-SVG, image-to-SVG, style transfer). Built on real-world data from **24** application domains with systematic complexity stratification, SVGenius evaluates models through **8** task categories and **18** metrics. We assess **22** mainstream models spanning different scales, architectures, training paradigms, and accessibility levels.
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<!-- <img src="docs/static/images/overview.jpg" width="100%"/> -->
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We introduce SVGenius, the first large-scale complexity-stratified benchmark accessing (M)LLMs capabilities across three progressive dimensions: **Understanding** (perceptua and semantic QA), **Editing** (bug fixing, code optimization, style editing), and **Generation** (text-to-SVG, image-to-SVG, style transfer). Built on real-world data from **24** application domains with systematic complexity stratification, SVGenius evaluates models through **8** task categories and **18** metrics. We assess **22** mainstream models spanning different scales, architectures, training paradigms, and accessibility levels.
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<!-- <img src="docs/static/images/overview.jpg" width="100%"/> -->
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The dataset contains the following fields:
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| Field Name | Description |
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| :--------- | :---------- |
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| `id` | Unique identifier for each SVG icon sample |
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| `filename` | Original filename of the SVG file, preserving the source naming convention with category and identifier information |
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| `difficulty` | Complexity level of the SVG icon, includes 3 distinct categories: `easy`, `medium`, and `hard` for evaluating different levels of SVG processing capabilities |
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| `svg_code` | Complete SVG markup code containing the vector graphics definition, including all paths,styles, and attributes |
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- **Language(s) (NLP):** en, zh
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- **License:** mit
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