OPTML-Group/Diffusion-MU-Attack

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Python
License
MIT License
Created 11 months ago
Updated about 2 months ago

OPTML-Group/Diffusion-MU-Attack

OPTML-Group

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The official implementation of ECCV'24 paper "To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now". This work introduces one fast and effective attack method to evaluate the harmful-content generation ability of safety-driven unlearned diffusion models.

BiP

[NeurIPS22] "Advancing Model Pruning via Bi-level Optimization" by Yihua Zhang*, Yuguang Yao*, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, and Sijia Liu

Unlearn-Saliency

[ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation" by Chongyu Fan*, Jiancheng Liu*, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu

Fast-BAT

[ICML22] "Revisiting and Advancing Fast Adversarial Training through the Lens of Bi-level Optimization" by Yihua Zhang*, Guanhua Zhang*, Prashant Khanduri, Mingyi Hong, Shiyu Chang, and Sijia Liu

Unlearn-Sparse

[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

ILM-VP

[CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zhang, and Sijia Liu

DeepZero

[ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu

AdvUnlearn

Official implementation of "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models"

Jupyter Notebook

RED-adv

"Can Adversarial Examples Be Parsed to Reveal Victim Model Information?" by Yuguang Yao*, Jiancheng Liu*, Yifan Gong*, Xiaoming Liu, Yanzhi Wang, Xue Lin, Sijia Liu

CLAW-SAT

Code repository for the SANER 2023 paper CLAWSAT: Towards Both Robust and Accurate Code Models.

Black-Box-Defense

[ICLR22] "How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective" by Yimeng Zhang, Yuguang Yao, Jinghan Jia, Jinfeng Yi, Mingyi Hong, Shiyu Chang, Sijia Liu

RED-ICLR22

[ICLR22] "Reverse Engineering of Imperceptible Adversarial Image Perturbations" by Yifan Gong*, Yuguang Yao*, Yize Li, Yimeng Zhang, Xiaoming Liu, Xue Lin, Sijia Liu

Robust-MoE-CNN

[ICCV23] Robust Mixture-of-Expert Training for Convolutional Neural Networks by Yihua Zhang, Ruisi Cai, Tianlong Chen, Guanhua Zhang, Huan Zhang, Pin-Yu Chen, Shiyu Chang, Zhangyang (Atlas) Wang, Sijia Liu

Fairness-Reprogramming

[NeurIPS 22] "Fairness Reprogramming" by Guanhua Zhang*, Yihua Zhang*, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang

OPTML-Group.github.io

BackdoorMSPC

[ICLR2024]"Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency" by Soumyadeep Pal, Yuguang Yao, Ren Wang, Bingquan Shen, Sijia Liu