We propose a probabilistic perspective on adversarial examples, allowing us to embed subjective understanding of semantics as a distribution into the process of generating adversarial examples, in a principled manner.

In this paper, we introduce a novel one-step drag-based image editing method, i.e., FastDrag, to accelerate the editing process.

In our case, we have only one object class ("insect") so the

The success of these fully deterministic models calls into question the community's understanding of diffusion models, which relies on noise in either gradient Langevin

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However, achieving one-shot generation that aligns with the user's intent is nearly impossible, yet