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Found 3 papers, 2 papers with code
When Does Group Invariant Learning Survive Spurious Correlations?
Motivated by this, we design a new group invariant learning method, which constructs groups with statistical independence tests, and reweights samples by group label proportion to meet the criteria.
Uncertainty Calibration for Ensemble-Based Debiasing Methods
Ensemble-based debiasing methods have been shown effective in mitigating the reliance of classifiers on specific dataset bias, by exploiting the output of a bias-only model to adjust the learning target.
On Layer Normalization in the Transformer Architecture
This motivates us to remove the warm-up stage for the training of Pre-LN Transformers.
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