Datasets:
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
authorship obfuscation
authorship attribution
authorship classification
authorship style
style transfer
style
License:
Update README.md
Browse files
README.md
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task_categories:
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- text-classification
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- text-generation
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-
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task_categories:
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- text-classification
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- text-generation
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language:
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- en
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tags:
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- authorship obfuscation
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- authorship attribution
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- authorship classification
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- authorship style
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- style transfer
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- style
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- author
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---
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# [StyleRemix] AuthorMix Dataset
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## Dataset Description
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This contains the AuthorMix dataset, which is created for authorship obfuscation. It includes data from four distinct domains: presidential speeches, early-1900s fiction novels, scholarly articles, and diary-style blogs. Altogether, AuthorMix contains over 30k high-quality paragraphs from 14 authors.
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This work was created in the paper: StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements (https://arxiv.org/abs/2408.15666v1), which should be cited if used in future work.
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Please see our paper (https://arxiv.org/abs/2408.15666v1) or Github repository (https://github.com/jfisher52/StyleRemix) for more details!
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### Dataset Summary
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For the presidential domain, we curate and clean speeches from George W. Bush, Barack Obama, and Donald Trump. For novel domain, we choose a collection of early 1900s fiction writers with strong writing styles: Ernest Hemingway, F. Scott Fitzgerald, and Virginia Woolf. We select these presidents/authors due to their diverse styles but similar eras to minimize content discrepancies.
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Lastly, we alter two existing datasets to match the formality of our new domains: the Extended-Brennan Greenstad, a collection of "scholarly" short (500-word) paragraphs gathered from Amazon Mechanical Turk (AMT), and the Blog Authorship corpus, a collection of blogs (diary-style entries) that were posted to blog.com.
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## Other Helpful Links
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Please see this Huggingface Collection (https://huggingface.co/collections/hallisky/authorship-obfuscation-66564c1c1d59bb62eaaf954f) if you want to access any other artifacts from the StyleRemix paper.
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## Citing Our Work
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Please cite our paper if you use this dataset or other resources:
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```
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@misc{fisher2024styleremixinterpretableauthorshipobfuscation,
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title={StyleRemix: Interpretable Authorship Obfuscation via Distillation and Perturbation of Style Elements},
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author={Jillian Fisher and Skyler Hallinan and Ximing Lu and Mitchell Gordon and Zaid Harchaoui and Yejin Choi},
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year={2024},
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eprint={2408.15666},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2408.15666},
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}
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```
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