zzha6204/RU-AI-origin

---
language:
- en
license: cc
size_categories:
- 1M<n<10M
task_categories:
- any-to-any
---

# RU-AI: A Large Multimodal Dataset for Machine Generated Content Detection

This is the noise agumented data for paper: [RU-AI: A Large Multimodal Dataset for Machine Generated Content Detection](https://arxiv.org/abs/2406.04906)

The original dataset is avaliable at zenodo and HuggingFace:
```url
https://zenodo.org/records/11406538
```
```url
https://huggingface.co/datasets/zzha6204/RU-AI-origin
```

The official repo is avaliable at:
```url
https://github.com/ZhihaoZhang97/RU-AI
```

## Reference
We are appreciated the open-source community for the datasets and the models.

[Microsoft COCO: Common Objects in Context](https://arxiv.org/abs/1405.0312)

[Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics ](https://www.jair.org/index.php/jair/article/view/10833)

[Learning Deep Features for Scene Recognition using Places Database](https://papers.nips.cc/paper_files/paper/2014/hash/3fe94a002317b5f9259f82690aeea4cd-Abstract.html)

[Text-Free Image-to-Speech Synthesis Using Learned Segmental Units](https://arxiv.org/abs/2012.15454)

[Unsupervised Learning of Spoken Language with Visual Context](https://papers.nips.cc/paper_files/paper/2016/hash/82b8a3434904411a9fdc43ca87cee70c-Abstract.html)

[Learning Word-Like Units from Joint Audio-Visual Analysis](https://aclanthology.org/P17-1047/)

[LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment](https://arxiv.org/abs/2310.01852)

[ImageBind: One Embedding Space To Bind Them All](https://openaccess.thecvf.com/content/CVPR2023/papers/Girdhar_ImageBind_One_Embedding_Space_To_Bind_Them_All_CVPR_2023_paper.pdf)

## Citation
If found our dataset or research useful, please cite:
```text
@misc{huang2024ruai,
title={RU-AI: A Large Multimodal Dataset for Machine Generated Content Detection},
author={Liting Huang and Zhihao Zhang and Yiran Zhang and Xiyue Zhou and Shoujin Wang},
year={2024},
eprint={2406.04906},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```