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Debias Anything: Fairness with Diversity without Supervision in Diffusion Models

d'Audiffret, Théau et al.
arXiv (All) · Papers
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machine-learning
Although diffusion models produce high-quality images, they also reproduce and amplify demographic imbalances in their training data. Debiasing their generation process post-training w.r.t. some sensitive attribute usually relies on classifier guidance or explicit text extra-conditioning, but this r
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