2025
Bias in Gender Bias Benchmarks: How Spurious Features Distort Evaluation
ICCV 2025poster
Gender bias in vision-language foundation models (VLMs) raises concerns about their safe deployment and is typically evaluated using benchmarks with gender annotations on real-world images. However, as these benchmarks often contain spurious correlations between gender and non-gender features, such…