Update README.md

README.md

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 # PerMed-MM: A Multimodal, Multi-Specialty Persian Medical Benchmark
 
-[**🤗 Dataset**](https://huggingface.co/datasets/universitytehran/PerMed-MM) | [**📖 Paper (Link)**]
+[**🤗 Dataset**](https://huggingface.co/datasets/universitytehran/PerMed-MM) | [**📖 Paper**](https://aclanthology.org/2025.ijcnlp-short.21/) | [**📄 PDF**](https://aclanthology.org/2025.ijcnlp-short.21.pdf)
 
 ## Dataset Description
 
-**PerMed-MM** is the first multimodal, multi-specialty benchmark for evaluating Vision Language Models (VLMs) on **Persian** medical question answering.
+**PerMed-MM** is a multimodal, multi-specialty benchmark designed to evaluate Vision Language Models (VLMs) on Persian medical question answering. 
 
-The dataset comprises **733 multiple-choice questions** sourced from the Iranian National Medical Board Exams. Each question is paired with **one to five clinically relevant images**, totaling **944 images**. The benchmark spans **46 medical specialties** and covers a wide range of visual modalities, including radiographic images, histopathology slides, dermatologic photographs, and ECG waveforms.
+The dataset consists of **733 multiple-choice questions** sourced from the Iranian National Medical Board Exams (years 2021 and 2023). Each question is paired with **1 to 5 clinically relevant images**, totaling **944 images** across **46 medical specialties** and multiple visual modalities.
 
+---
+
+## Dataset Statistics
+
+### Image Modality Distribution
+| Image Modality | Count | Percentage (%) |
+| :--- | :---: | :---: |
+| Microscopic Pathology | 175 | 18.5% |
+| Charts, Diagrams & Tables | 138 | 14.6% |
+| X-ray | 131 | 13.9% |
+| CT | 115 | 12.2% |
+| Clinical / Gross Photography | 97 | 10.3% |
+| Ultrasound | 76 | 8.1% |
+| Electrophysiology (ECG / EEG) | 73 | 7.7% |
+| Nuclear Medicine | 72 | 7.6% |
+| MRI | 46 | 4.9% |
+| Endoscopy | 21 | 2.2% |
+
+### Images per Question
+- **1 image:** 82.3% (603 questions)
+- **2 images:** 11.3% (83 questions)
+- **3 images:** 2.0% (15 questions)
+- **4 images:** 4.1% (30 questions)
+- **5 images:** 0.3% (2 questions)
+
+---
+
+## Citation
+
+If you use this dataset or find it helpful in your research, please cite our paper:
 
+```bibtex
+@inproceedings{khoramfar-etal-2025-permed,
+    title = "{P}er{M}ed-{MM}: A Multimodal, Multi-Specialty {P}ersian Medical Benchmark for Evaluating Vision Language Models",
+    author = "Khoramfar, Ali  and Dousti, Mohammad Javad  and Faili, Heshaam",
+    booktitle = "Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics",
+    month = dec,
+    year = "2025",
+    address = "Mumbai, India",
+    publisher = "The Asian Federation of Natural Language Processing and The Association for Computational Linguistics",
+    url = "https://aclanthology.org/2025.ijcnlp-short.21/",
+    doi = "10.18653/v1/2025.ijcnlp-short.21",
+    pages = "232--241",
+    ISBN = "979-8-89176-299-2"
+}
+```