Papers with generalization ability of fine-tuned models
Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding (2022.emnlp-main)
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| Challenge: | Existing approaches to reduce dataset bias rely on spurious correlations and obstruct valid feature information while mitigating bias. |
| Approach: | They propose a representation normalization method which disentangles correlations between features of encoded sentences and a kernel approximation method which provides isotropic data distribution. |
| Outcome: | The proposed method eliminates the bias problem by providing isotropic data distribution while maintaining in-distribution accuracy. |