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--- |
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license: mit |
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language: |
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- en |
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--- |
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<h1 align="center">Vis-IR: Unifying Search With Visualized Information Retrieval</h1> |
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<p align="center"> |
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<a href="https://arxiv.org/abs/2502.11431"> |
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<img alt="Build" src="http://img.shields.io/badge/arXiv-2502.11431-B31B1B.svg"> |
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</a> |
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<a href="https://github.com/VectorSpaceLab/Vis-IR"> |
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<img alt="Build" src="https://img.shields.io/badge/Github-Code-blue"> |
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</a> |
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<a href="https://huggingface.co/datasets/marsh123/VIRA/"> |
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<img alt="Build" src="https://img.shields.io/badge/🤗 Datasets-VIRA-yellow"> |
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</a> |
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<a href="https://huggingface.co/datasets/marsh123/MVRB"> |
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<img alt="Build" src="https://img.shields.io/badge/🤗 Datasets-MVRB-yellow"> |
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</a> |
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<!-- <a href=""> |
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<img alt="Build" src="https://img.shields.io/badge/🤗 Model-UniSE CLIP-yellow"> |
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</a> --> |
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<a href="https://huggingface.co/marsh123/UniSE"> |
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<img alt="Build" src="https://img.shields.io/badge/🤗 Model-UniSE MLLM-yellow"> |
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</a> |
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</p> |
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## Overview |
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**VIRA** (Vis-IR Aggregation), a large-scale dataset comprising a vast collection of screenshots from diverse sources, carefully curated into captioned and questionanswer formats. |
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## Statistics |
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There are three types of data in VIRA: caption data, query-to-screenshot (q2s) data, and screenshot+query-to-screenshot (sq2s) data. The table below provides a detailed breakdown of the data counts for each domain and type. |
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## Organization Structure |
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The dataset is organized in the following structure: |
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```tree |
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Domain/ |
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├── caption.jsonl: a screenshot image path and its corresponding caption |
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├── q2s.jsonl: a query, a positive screenshot and eight negative screenshots |
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├── sq2s.jsonl: a query, a query screenshot, a positive screenshot and eight negative screenshots |
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└── images/ |
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├── image1.jpg |
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├── image2.jpg |
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... |
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``` |
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_Due to the large number of images, uploading all of them takes time. Currently, the upload is not yet complete, and we will continue the process._ |
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## License |
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VIRA is licensed under the [MIT License](LICENSE). |
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## Citation |
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If you find this dataset useful, please cite: |
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``` |
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@article{liu2025any, |
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title={Any Information Is Just Worth One Single Screenshot: Unifying Search With Visualized Information Retrieval}, |
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author={Liu, Ze and Liang, Zhengyang and Zhou, Junjie and Liu, Zheng and Lian, Defu}, |
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journal={arXiv preprint arXiv:2502.11431}, |
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year={2025} |
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} |
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``` |
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