Papers by Remi Tachet des Combes
Increasing Robustness to Spurious Correlations using Forgettable Examples (2021.eacl-main)
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| Challenge: | Neural NLP models often exploit spurious correlations to perform tasks. minority examples have been shown to increase the out-of-distribution generalization of pre-trained language models. |
| Approach: | They propose to use example forgetting to find minority examples without prior knowledge of spurious correlations in the dataset. |
| Outcome: | The proposed approach improves out-of-distribution generalization on minorities . it shows that minority examples are more robust on challenging datasets . |