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README.md
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@@ -9,6 +9,59 @@ This model was obtained by fine-tuning [roberta-large](https://huggingface.co/ro
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Paper: [Understanding Iterative Revision from Human-Written Text](https://arxiv.org/abs/2203.03802) <br>
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Authors: Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, Dongyeop Kang
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## Usage
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```python
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import torch
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Paper: [Understanding Iterative Revision from Human-Written Text](https://arxiv.org/abs/2203.03802) <br>
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Authors: Wanyu Du, Vipul Raheja, Dhruv Kumar, Zae Myung Kim, Melissa Lopez, Dongyeop Kang
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## Edit Intention Prediction Task
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Given a pair of original sentence and revised sentence, our model can predict the edit intention for this revision pair.<br>
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More specifically, the model will predict the probability of the following edit intentions:
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<table style="width:90%">
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<tr>
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<th>Edit Intention</th>
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<th>Definition</th>
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<th>Example</th>
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</tr>
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<tr>
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<td>clarity</td>
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<td>Make the text more formal, concise, readable and understandable.</td>
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<td>
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Original: The changes made the paper better than before. <br>
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Revised: The changes improved the paper.
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</td>
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</tr>
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<tr>
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<td>fluency</td>
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<td>Fix grammatical errors in the text.</td>
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<td>
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Original: She went to the markt. <br>
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Revised: She went to the market.
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</td>
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</tr>
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<tr>
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<td>coherence</td>
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<td>Make the text more cohesive, logically linked and consistent as a whole.</td>
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<td>
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Original: She works hard. She is successful. <br>
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Revised: She works hard; therefore, she is successful.
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</td>
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</tr>
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<tr>
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<td>style</td>
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<td>Convey the writer’s writing preferences, including emotions, tone, voice, etc..</td>
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<td>
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Original: Everything was rotten. <br>
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Revised: Everything was awfully rotten.
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</td>
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</tr>
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<tr>
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<td>meaning-changed</td>
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<td>Update or add new information to the text.</td>
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<td>
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Original: This method improves the model accuracy from 64% to 78%. <br>
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Revised: This method improves the model accuracy from 64% to 83%.
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</td>
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</tr>
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</table>
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## Usage
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```python
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import torch
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