Papers by Yusu Qian
Reducing Gender Bias in Word-Level Language Models with a Gender-Equalizing Loss Function (P19-2)
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| Challenge: | Existing methods to reduce gender bias in natural language datasets are inadequate. |
| Approach: | They propose a loss function modification approach which equalizes the probabilities of male and female words in the output. |
| Outcome: | The proposed approach outperforms existing methods in several aspects, especially in reducing gender bias in occupation words. |
Story-level Text Style Transfer: A Proposal (2020.acl-srw)
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| Challenge: | Text style transfer is a task that aims to change the style of input text to the target style while preserving the content to some extent. |
| Approach: | They propose to use story-level text style transfer to generate stories that preserve plot . they propose to employ BERT-based method, Story Realization method, and Graph-based methods . |
| Outcome: | The proposed method preserves the plot of the input story while exhibiting a strong target style. |
Gender Stereotypes Differ between Male and Female Writings (P19-2)
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| Challenge: | a new study quantitatively evaluates gender stereotypes in written language . female writings contain fewer gender stereotype scores than male writings . |
| Approach: | They quantitatively evaluate and analyze gender stereotypes in written language . they compare writings by female authors with writings from male authors . |
| Outcome: | The results show that writings by female authors have lower gender stereotype scores . the authors plan on using more datasets over the past century to study gender stereotypes . |