Add dataset description, task categories, and usage examples

README.md

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 ---
 license: cc-by-4.0
+task_categories:
+- text-retrieval
+- image-text-to-text
 configs:
 - config_name: cvqa
   data_files:
@@ -63,4 +66,49 @@ dataset_info:
   download_size: 1014718726
   dataset_size: 1861309171
 ---
-Sorry exam week, will be updated soon!
+
+# M4-RAG: A Massive-Scale Multilingual Multi-Cultural Multimodal RAG
+
+[**Paper**](https://huggingface.co/papers/2512.05959) | [**Code**](https://github.com/davidanugraha/M4-RAG)
+
+M4-RAG is a massive-scale benchmark spanning 42 languages, 56 regional dialects and registers, and 189 countries, comprising over 80,000 culturally diverse image-question pairs for evaluating retrieval-augmented Visual Question Answering (VQA) across languages and modalities. 
+
+This repository specifically contains the **Wikipedia Retrieval Corpus**, a controlled retrieval environment containing millions of carefully curated multilingual documents relevant to the query domains.
+
+## Dataset Structure
+
+The dataset consists of two configurations:
+- `cvqa`: Wikipedia articles relevant to the Culturally-Aware Visual Question Answering domain.
+- `worldcuisines`: Wikipedia articles relevant to the food-related visual question answering domain.
+
+## Sample Usage
+
+You can load the retrieval corpus using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load the CVQA Wikipedia retrieval corpus
+cvqa_corpus = load_dataset("davidanugraha/M4-RAG", "cvqa", split="train")
+
+# Load the WorldCuisines Wikipedia retrieval corpus
+worldcuisines_corpus = load_dataset("davidanugraha/M4-RAG", "worldcuisines", split="train")
+```
+
+## Related Datasets
+- **CVQA Images**: Available at [`davidanugraha/cvqa`](https://huggingface.co/datasets/davidanugraha/cvqa)
+- **WorldCuisines Images**: Available at [`worldcuisines/vqa-v1.1`](https://huggingface.co/datasets/worldcuisines/vqa-v1.1)
+
+## Citation
+
+If you use M4-RAG in your research, please cite:
+
+```bibtex
+@article{anugraha2025m4rag,
+  title={M4-RAG: A Massive-Scale Multilingual Multi-Cultural Multimodal RAG},
+  author={Anugraha, David and Irawan, Patrick Amadeus and Singh, Anshul and Lee, En-Shiun Annie and Winata, Genta Indra},
+  journal={arXiv preprint arXiv:2512.05959},
+  year={2025},
+  url={https://arxiv.org/abs/2512.05959}
+}
+```