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  # 🧠 CalliReader: Contextualizing Chinese Calligraphy via an Embedding-aligned Vision Language Model
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  <div align="center">
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  <a href="https://github.com/LoYuXr/CalliReader">📂 Code</a>
 
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  </div>
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  **CalliBench** is aimed to comprehensively evaluate VLMs' performance on the recognition and understanding of Chinese calligraphy.
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  * Certain samples include **contextual VQA**.
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  ## 🧪 How To Use
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- **.parqeut** files of different tiers can be found in the sub-folders of **data**. **Pandas** can be used to parse and further process those files.
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  For example, to load a sample and convert its image into a .jpg file:
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  ```
 
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  # 🧠 CalliReader: Contextualizing Chinese Calligraphy via an Embedding-aligned Vision Language Model
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  <div align="center">
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  <a href="https://github.com/LoYuXr/CalliReader">📂 Code</a>
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+ <a href="https://arxiv.org/pdf/2503.06472">📄 Paper</a>
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  </div>
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  **CalliBench** is aimed to comprehensively evaluate VLMs' performance on the recognition and understanding of Chinese calligraphy.
 
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  * Certain samples include **contextual VQA**.
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  ## 🧪 How To Use
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+ All **.parqeut** files of different tiers can be found in the sub-folders of **data**. **Pandas** can be used to parse and further process those files.
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  For example, to load a sample and convert its image into a .jpg file:
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  ```