DiFair
Introduced by Zakizadeh et al. in DiFair: A Benchmark for Disentangled Assessment of Gender Knowledge and Bias
DiFair serves as a meticulous endeavor to address the oversight in evaluating the impact of bias mitigation on useful gender knowledge while assessing gender neutrality in pretrained language models. This metric delves into not only quantifying a model's biased tendencies but also assessing the preservation of useful gender knowledge.
Papers
| Paper | Code | Results | Date | Stars |
|---|
Dataset Loaders
No data loaders found. You can
submit your data loader here.
No data loaders found. You can
submit your data loader here.
