anyangsong/MAGA-human-source

This is a mirror of the sourced human text datasets used for our MAGA.

Please note that this is a mirror of the original source, and some of the data in it needs to be cleaned before use. For more details, please refer to our GitHub.

domain	source
Reddit	https://huggingface.co/datasets/sentence-transformers/reddit-title-body
S2ORC	https://huggingface.co/datasets/sentence-transformers/s2orc
Wikipedia	https://huggingface.co/datasets/aadityaubhat/GPT-wiki-intro
wikiHow	https://modelscope.cn/datasets/sentence-transformers/wikihow
Trustpilot	https://huggingface.co/datasets/Kerassy/trustpilot-reviews-123k
Amazon Reviews	https://huggingface.co/datasets/sentence-transformers/amazon-reviews
Yahoo Answers	https://huggingface.co/datasets/sentence-transformers/yahoo-answers
Natural Questions	https://huggingface.co/datasets/sentence-transformers/natural-questions
CC News	https://huggingface.co/datasets/sentence-transformers/ccnews
NPR News	https://huggingface.co/datasets/sentence-transformers/npr
Baidu Tieba (百度贴吧)	https://huggingface.co/datasets/HongzheBi/DuReader2.0
Weibo Review（微博评论）	https://huggingface.co/datasets/LZYFirecn/weibo-hot-search
Rednote Review（小红书评论）	https://huggingface.co/datasets/Jingyi77/CHASM-Covert_Advertisement_on_RedNote
CSL（中文核心期刊摘要）	https://github.com/ydli-ai/CSL
Baidu Baike (百度百科)	https://huggingface.co/datasets/lars1234/baidu-baike-dataset
Dianping（大众点评）	https://huggingface.co/datasets/twn39/dianping
Douban Review (豆瓣评论)	https://huggingface.co/datasets/dirtycomputer/douban_movie_review
Baidu Zhidao (百度知道)	https://huggingface.co/datasets/HongzheBi/DuReader2.0
Zhihu（知乎）	https://huggingface.co/datasets/suolyer/zhihu
CLTS（澎湃新闻）	https://github.com/lxj5957/CLTS-Dataset

Citation

If you find MAGA useful for your research and applications, please cite using the Bibtex:

@misc{song2026maga,
      title={MAGA-Bench: Machine-Augment-Generated Text via Alignment Detection Benchmark}, 
      author={Anyang Song and Ying Cheng and Yiqian Xu and Rui Feng},
      year={2026},
      eprint={2601.04633},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2601.04633}, 
}