Papers with automated augmentation method
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers (2023.acl-long)
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| Challenge: | toxicity and IMDB review datasets show that pre-trained NLP classifiers learn spurious correlations between input features and label . |
| Approach: | They propose an algorithm to regularize the learnt effect of features on the model’s prediction to the estimated effect of a feature on label. |
| Outcome: | The proposed method minimises spurious correlations and improves minority group accuracy while improving total accuracy compared to standard training. |