RG-TTA uses reinforcement learning at test time to gate fairness regularization by estimated bias sensitivity, reducing stereotypes on FairFace and UTKFace while improving zero-shot utility.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , month = nov, year =
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Selective Test-Time Debiasing for CLIP via Reward Gating
RG-TTA uses reinforcement learning at test time to gate fairness regularization by estimated bias sensitivity, reducing stereotypes on FairFace and UTKFace while improving zero-shot utility.