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  # Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
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- ### [Project Website]() | [Arxiv Preprint](https://arxiv.org/abs/2405.15234) | [Fine-tuned Weights](https://drive.google.com/drive/folders/1Nf-EJ2W3CsZwpc5blZFi7tm7o1wEiTg4?usp=sharing) | [Demo]() <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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  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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