Papers with latent content encoding
Text Style Transfer for Bias Mitigation using Masked Language Modeling (2022.naacl-srw)
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| Challenge: | Various research findings have concluded that biased textual data has significant effects on target demographic groups. |
| Approach: | They propose a text-style transfer model that can be trained on non-parallel data and be used to automatically mitigate bias in textual data. |
| Outcome: | The proposed model improves on limitations of existing methods while maintaining good style transfer accuracy. |