maximuspowers
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README.md
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return json.dumps(result, indent=4)
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```
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return json.dumps(result, indent=4)
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```
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## GUS-Net Project Details:
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#### Resources:
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- 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).
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- 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).
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#### Please cite:
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```
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@article{powers2024gusnet,
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title={{GUS-Net: Social Bias Classification in Text with Generalizations, Unfairness, and Stereotypes}},
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author={Maximus Powers and Umang Mavani and Harshitha Reddy Jonala and Ansh Tiwari and Hua Wei},
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journal={arXiv preprint arXiv:2410.08388},
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year={2024},
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url={https://arxiv.org/abs/2410.08388}
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}
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```
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Give our research group, [Ethical Spectacle](https://huggingface.co/ethical-spectacle), a follow ;).
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