AI RESEARCH
Test-Time Collective Action: Proxy-Based Perturbations for Correcting Algorithmic Harms
arXiv CS.LG
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ArXi:2605.27689v1 Announce Type: new When machine learning systems under-perform for particular subgroups, affected users typically have no way to correct these disparities without relying on platform-level fixes. Existing approaches to algorithmic fairness rely on provider-centric approaches to correct these failures, leaving users with no external lever when faced with harm.