4 citations · 8 across the 6 of their papers we have counts for
3 papers · 1 filter
Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
Yiwei Yang, Chung Peng Lee, Shangbin Feng +5
Finetuning can cause spurious correlations to arise between non-essential features and the target labels, but benchmarks to study these effects involve contrived settings and narro…
Resampled Datasets Are Not Enough: Mitigating Societal Bias Beyond Single Attributes
Yusuke Hirota, Jerone T. A. Andrews, Dora Zhao +4
We tackle societal bias in image-text datasets by removing spurious correlations between protected groups and image attributes. Traditional methods only target labeled attributes,…
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets
Angelina Wang, Alexander Liu, Ryan Zhang +6
Machine learning models are known to perpetuate and even amplify the biases present in the data. However, these data biases frequently do not become apparent until after the models…