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cs.CV2025
A Framework for Benchmarking Fairness-Utility Trade-offs in Text-to-Image Models via Pareto Frontiers
Marco N. Bochernitsan, Rodrigo C. Barros, Lucas S. Kupssinskü
Achieving fairness in text-to-image generation demands mitigating social biases without compromising visual fidelity, a challenge critical to responsible AI. Current fairness evalu…
cs.GR2025
Inference Time Debiasing Concepts in Diffusion Models
Lucas S. Kupssinskü, Marco N. Bochernitsan, Jordan Kopper +2
We propose DeCoDi, a debiasing procedure for text-to-image diffusion-based models that changes the inference procedure, does not significantly change image quality, has negligible…