SIRUS is a training-free, inference-time framework that suppresses target concepts in text-to-video diffusion models via subspace-informed prompt projection and residual subtraction, with a new video-centric unlearning evaluation framework.
Reliable and efficient concept erasure of text-to-image diffusion models
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Inference-Time Concept Suppression and Video-Centric Evaluation for Text-to-Video Models
SIRUS is a training-free, inference-time framework that suppresses target concepts in text-to-video diffusion models via subspace-informed prompt projection and residual subtraction, with a new video-centric unlearning evaluation framework.