Presents Decoupled Time Guidance (DTG) for training-free generative video super-resolution by temporally decoupling conditional and unconditional diffusion signals.
Mist: Mitigating intersectional bias with disentangled cross- attention editing in text-to-image diffusion models.arXiv preprint arXiv:2403.19738, 2024
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TES applies early global alignment then iterative CLIP-guided refinement to text embeddings in Stable Diffusion to mitigate bias while preserving quality.
DebFilter mitigates biases in text-to-image diffusion models by applying a fixed offset to the guidance embedding slice in cross-attention during inference.
citing papers explorer
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DTG-Restore: Training-Free Diffusion Refinement for Generative Video Super-Resolution
Presents Decoupled Time Guidance (DTG) for training-free generative video super-resolution by temporally decoupling conditional and unconditional diffusion signals.
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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.
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DebFilter: Eradicating Biases Stashed in Value
DebFilter mitigates biases in text-to-image diffusion models by applying a fixed offset to the guidance embedding slice in cross-attention during inference.