16 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.CY2024
DrawL: Understanding the Effects of Non-Mainstream Dialects in Prompted Image Generation
Joshua N. Williams, Molly FitzMorris, Osman Aka +1
Text-to-image models are now easy to use and ubiquitous. However, prior work has found that they are prone to recapitulating harmful Western stereotypes. For example, requesting th…
cs.AI2022★ 1 cited
Visual Identification of Problematic Bias in Large Label Spaces
Alex Bäuerle, Aybuke Gul Turker, Ken Burke +4
While the need for well-trained, fair ML systems is increasing ever more, measuring fairness for modern models and datasets is becoming increasingly difficult as they grow at an un…
cs.CV2021★ 16 cited
Measuring Model Biases in the Absence of Ground Truth
Osman Aka, Ken Burke, Alex Bäuerle +2
The measurement of bias in machine learning often focuses on model performance across identity subgroups (such as man and woman) with respect to groundtruth labels. However, these…