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# Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
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Paper can be checked in [Arxiv Preprint](https://arxiv.org/abs/2405.15234). <br>
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Our proposed robust unlearning framework, AdvUnlearn, enhances diffusion models' safety by robustly erasing unwanted concepts through adversarial training, achieving an optimal balance between concept erasure and image generation quality.
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# Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
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Paper can be checked in [Arxiv Preprint](https://arxiv.org/abs/2405.15234). <br>
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Code can be checked in [GitHub](https://github.com/OPTML-Group/AdvUnlearn). <br>
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Our proposed robust unlearning framework, AdvUnlearn, enhances diffusion models' safety by robustly erasing unwanted concepts through adversarial training, achieving an optimal balance between concept erasure and image generation quality.
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