TES applies early global alignment then iterative CLIP-guided refinement to text embeddings in Stable Diffusion to mitigate bias while preserving quality.
Model-agnostic gender bias control for text-to- image generation via sparse autoencoder.arXiv preprint arXiv:2507.20973, 2025
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Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization
TES applies early global alignment then iterative CLIP-guided refinement to text embeddings in Stable Diffusion to mitigate bias while preserving quality.