15 citations · 41 across the 4 of their papers we have counts for
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cs.LG2022★ 12 cited
Contrastive Adapters for Foundation Model Group Robustness
Michael Zhang, Christopher Ré
While large pretrained foundation models (FMs) have shown remarkable zero-shot classification robustness to dataset-level distribution shifts, their robustness to subpopulation or…
cs.LG2022★ 15 cited
Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations
Michael Zhang, Nimit S. Sohoni, Hongyang R. Zhang +2
Spurious correlations pose a major challenge for robust machine learning. Models trained with empirical risk minimization (ERM) may learn to rely on correlations between class labe…