ethical-spectacle/biased-corpus
收藏资源简介：
--- license: mit task_categories: - text-classification language: - en tags: - Social Bias pretty_name: Synthetic Corpus of Biased Statements size_categories: - 10K<n<100K --- ## GUS-Net Project Details: #### Resources: - Please visit this [collection](https://huggingface.co/collections/ethical-spectacle/gus-net-66edfe93801ea45d7a26a10f) for the datasets and model presented in the [GUS-Net paper](https://huggingface.co/papers/2410.08388). - GUS-Net was implemented as part of [The Fair-ly Project](https://ethical-spectacle-research.gitbook.io/fair-ly), in a [Chrome Extension](https://chromewebstore.google.com/detail/fair-ly/geoaacpcopfegimhbdemjkocekpncfcc), and [PyPI package](https://ethical-spectacle-research.gitbook.io/fair-ly/toolkit/python-package). #### Please cite: ``` @article{powers2024gusnet, title={{GUS-Net: Social Bias Classification in Text with Generalizations, Unfairness, and Stereotypes}}, author={Maximus Powers and Umang Mavani and Harshitha Reddy Jonala and Ansh Tiwari and Hua Wei}, journal={arXiv preprint arXiv:2410.08388}, year={2024}, url={https://arxiv.org/abs/2410.08388} } ``` Give our research group, [Ethical Spectacle](https://huggingface.co/ethical-spectacle), a follow ;).
许可证：MIT许可证 任务类别：文本分类 语言：英语 标签：社会偏见（Social Bias） 展示名称：带偏见陈述合成语料库（Synthetic Corpus of Biased Statements） 样本规模：10000 < n < 100000 ## GUS-Net 项目详情： ### 资源说明 - 请访问此[合集](https://huggingface.co/collections/ethical-spectacle/gus-net-66edfe93801ea45d7a26a10f)以获取GUS-Net论文[GUS-Net: Social Bias Classification in Text with Generalizations, Unfairness, and Stereotypes](https://huggingface.co/papers/2410.08388)中展示的数据集与模型。 - GUS-Net 作为Fair-ly项目的组成部分开发，可通过Chrome浏览器扩展程序（[链接](https://chromewebstore.google.com/detail/fair-ly/geoaacpcopfegimhbdemjkocekpncfcc)）以及PyPI软件包（[链接](https://ethical-spectacle-research.gitbook.io/fair-ly/toolkit/python-package)）获取使用。 ### 引用格式 @article{powers2024gusnet, title={{GUS-Net: Social Bias Classification in Text with Generalizations, Unfairness, and Stereotypes}}, author={Maximus Powers and Umang Mavani and Harshitha Reddy Jonala and Ansh Tiwari and Hua Wei}, journal={arXiv preprint arXiv:2410.08388}, year={2024}, url={https://arxiv.org/abs/2410.08388} } 欢迎关注我们的研究团队Ethical Spectacle（[Hugging Face主页](https://huggingface.co/ethical-spectacle)） ;)
