Unbiased Model Prediction Without Using Protected Attribute Information

ArXi:2603.29270v1 Announce Type: new The problem of bias persists in the deep learning community as models continue to provide disparate performance across different graphic subgroups. Therefore, several algorithms have been proposed to improve the fairness of deep models. However, a majority of these algorithms utilize the protected attribute information for bias mitigation, which severely limits their application in real-world scenarios.