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README.md

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 # MagicData340K: A Large-Scale Dataset for Fine-Grained Artifacts Assessment in Text-to-Image Generation
 
-This repository hosts **MagicData340K**, a large-scale human-annotated dataset central to the [MagicMirror framework](https://wj-inf.github.io/MagicMirror-page/). The MagicMirror framework introduces a comprehensive approach for the systematic and fine-grained evaluation of physical artifacts (such as anatomical and structural flaws) in Text-to-Image (T2I) generation.
+This repository hosts **MagicData340K**, a large-scale human-annotated dataset central to the [MagicMirror framework](https://wj-inf.github.io/MagicMirror-page). The MagicMirror framework introduces a comprehensive approach for the systematic and fine-grained evaluation of physical artifacts (such as anatomical and structural flaws) in Text-to-Image (T2I) generation.
 
 `MagicData340K` is the first human-annotated large-scale dataset, comprising 340,000 generated images, each with fine-grained artifact labels. These annotations are guided by a detailed taxonomy of generated image artifacts, making the dataset crucial for understanding and improving the perceptual quality of T2I models.
 
 **Paper**: [MagicMirror: A Large-Scale Dataset and Benchmark for Fine-Grained Artifacts Assessment in Text-to-Image Generation](https://arxiv.org/abs/2509.10260)
 
-**Project Page**: [https://wj-inf.github.io/MagicMirror-page/](https://wj-inf.github.io/MagicMirror-page/)
+**Project Page**: [https://wj-inf.github.io/MagicMirror-page/](https://wj-inf.github.io/MagicMirror-page)
 
 **Code (MagicMirror Benchmark)**: [https://github.com/wj-inf/MagicMirror](https://github.com/wj-inf/MagicMirror)
 
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 ## Related Hugging Face Assets
 
-*   **Dataset (Self-reference)**: [wj-inf/MagicData340k](https://huggingface.co/datasets/wj-inf/MagicData340k)
+*   **Dataset (Self-reference)**: [wj-inf/MagicData340k](https://huggingface.co/wj-inf/MagicData340k)
 *   **Model (MagicAssessor VLM)**: [wj-inf/MagicAssessor-7B](https://huggingface.co/datasets/wj-inf/MagicAssessor-7B)
 
 ## Sample Usage