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README.md

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+<div align="center" style="line-height: 1;">
+<h1>WAON: Large-Scale and High-Quality Japanese Image-Text Pair Dataset for Vision-Language Models </h1> 
+
+
+  |
+  <a href="https://huggingface.co/collections/llm-jp/waon" target="_blank">🤗 HuggingFace</a>
+  &nbsp;|
+  <a href="https://arxiv.org/abs/xxx" target="_blank">📄 Paper</a>
+  &nbsp;|
+  <a href="https://github.com/llm-jp/WAON" target="_blank">🧑‍💻 Code</a>
+  &nbsp;|
+
+  <br/>
+
+<img src="validation_top1_accuracy.svg" width="50%"/>
+</div>
+
+
+## Introduction
+WAON is a Japanese (image, text) pair dataset containing approximately 155M examples, crawled from Common Crawl.
+It is built from snapshots taken in 2025-18, 2025-08, 2024-51, 2024-42, 2024-33, and 2024-26.
+The dataset is high-quality and diverse, constructed through a sophisticated data processing pipeline.
+We apply filtering based on image size and SigLIP scores, and perform deduplication using URLs, captions, and perceptual hashes (pHash).
+
+## How to Use
+```python
+from datasets import load_dataset
+
+ds = load_dataset("llm-jp/WAON-CC-Pair")
+```
+
+### Format
+
+- `url`: URL of the image
+- `caption`: Caption associated with the image
+- `page_title`: Title of the page containing the image
+- `page_url`: URL of the page
+- `punsafe`: Probability that the image is unsafe
+- `quality`: The quality of the text in the text column
+- `width`: Width (in pixels) of the resized image used for computing pHash
+- `height`: Height (in pixels) of the resized image used for computing pHash
+- `original_width`: Original width of the image
+- `original_height`: Original height of the image
+- `sha256`: SHA-256 hash of the original image file
+- `phash`: Perceptual hash (pHash) computed from the resized image
+
+
+## Dataset Construction Pipeline
+
+We construct WAON dataset through the following steps:
+<div align="center">
+<img src="waon-pipeline.svg" width="50%"/>
+</div>
+
+## Citation
+
+```bibtex
+```