arXiv stat.ML
· Papers
How Reliable are Fairness Audits with Unreliable Data?
arXiv:2506.23033v4 Announce Type: replace-cross Abstract: Fairness audits are a key component of responsible machine-learning deployment. Yet, audit-recommendation reliability under incomplete protected-label access is still poorly understood. In this work, we focused on protected-label missingness in fairness mitigati