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@@ -3,4 +3,28 @@ Official Code for 'EPiDA: An Easy Plug-in Data Augmentation Framework for High P
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NAACL 2022 Accepted Paper
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The code will be gradually open source!
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## :e-mail: Contact :e-mail:
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Feel free to contact me if you have any problems! [email protected]
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## :fire: 2. Quick Start :fire:
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Suppose you have already get a dataset, you can modify the code in train_sst_epida_eda.py or train_irony_epida_eda.py for quick start.
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```
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python3 train_irony_epida_eda.py
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```
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## :beers: Data Access :beers:
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The SST dataset can be achieved via [SUB2](https://home.ttic.edu/~freda/paper/shi2021substructure.pdf).
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The corpus used in major paper can be downloaded by checking the links given in the paper or email.
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## :satisfied: Citation :satisfied:
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If you find this project is useful for your research, please cite:
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```
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@article{zhao2022epida,
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title={EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification},
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author={Zhao, Minyi and Zhang, Lu and Xu, Yi and Ding, Jiandong and Guan, Jihong and Zhou, Shuigeng},
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journal={arXiv preprint arXiv:2204.11205},
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year={2022}
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}
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```

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