[Update] More methods added
Browse files- src/about.py +4 -1
src/about.py
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@@ -60,7 +60,10 @@ For more details of Unlearning Methods used in this benchmarks:
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- [concept-SemiPermeable Membrane (SPM)](https://github.com/Con6924/SPM);
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- [Saliency Unlearning (SalUn)](https://github.com/OPTML-Group/Unlearn-Saliency);
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- [EraseDiff (ED)](https://github.com/JingWu321/EraseDiff);
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- [ScissorHands (SH)](https://github.com/JingWu321/Scissorhands)
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<strong>We will evaluate your model on UnlearnDiffAtk Benchmark!</strong> \\
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Open a [github issue](https://github.com/OPTML-Group/Diffusion-MU-Attack/issues) or email us at zhan1853@msu.edu!
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- [concept-SemiPermeable Membrane (SPM)](https://github.com/Con6924/SPM);
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- [Saliency Unlearning (SalUn)](https://github.com/OPTML-Group/Unlearn-Saliency);
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- [EraseDiff (ED)](https://github.com/JingWu321/EraseDiff);
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- [ScissorHands (SH)](https://github.com/JingWu321/Scissorhands);
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- [Mass Concept Erasure (MACE)](https://github.com/Shilin-LU/MACE);
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- [Reliable and Efficient Concept Erasure (RECE)](https://github.com/CharlesGong12/RECE);
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- [Training-Free and Adaptive Guard (SAFREE)](https://github.com/jaehong31/SAFREE).
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<strong>We will evaluate your model on UnlearnDiffAtk Benchmark!</strong> \\
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Open a [github issue](https://github.com/OPTML-Group/Diffusion-MU-Attack/issues) or email us at zhan1853@msu.edu!
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