Update README.md

README.md

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 - art
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 - 1K<n<10K
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+---
+
+
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+# 🧠 CalliReader: Contextualizing Chinese Calligraphy via an Embedding-aligned Vision Language Model
+<div align="center">
+  <a href="https://github.com/LoYuXr/CalliReader">📂 Code</a>
+  <a href="https://arxiv.org/pdf/2503.06472">📄 Paper</a>
+</div>
+
+**CalliBench** is aimed to comprehensively evaluate VLMs' performance on the recognition and understanding of Chinese calligraphy. 
+
+
+
+## 📦 Dataset Summary
+
+* **Samples**: 3,192 image–annotation pairs
+* **Tasks**: **Full-page recognition** and **Contextual VQA** (choice of author/layout/style, bilingual interpretation, and intent analysis).
+* **Annotations**:
+  
+  * Metadata of author, layout, and style.
+  * Fine-grained annotations of **character-wise bounding boxes and labels**.
+  * Certain samples include **contextual VQA**.
+
+## 🧪 How To Use
+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.
+
+For example, to load a sample and convert its image into a .jpg file: 
+```
+import pandas as pd
+import io
+from PIL import Image
+df = pd.read_parquet('./data/train.parquet')
+image_data = df.iloc[0]['image'] 
+image = Image.open(io.BytesIO(image_data['bytes']))
+image.save('output_image.jpg') 
+```
+
+## 🤗 License
+
+Apache 2.0 – open for research and commercial use.