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The Tokens Strike Back: Safety-Aware Denoising with Directional Embedding-based Revision
The Safety-Aware Denoiser (SAD) is a recent, training-free, safety-guidance framework for text diffusion models. During inference, SAD steers text samples toward safe regions of the token probability space. In this paper, we propose $\mathit{SADDER}$ (Safety-Aware Denoising with Directional Embeddin
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