An Easy-to-use Knowledge Editing Framework for LLMs.
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Updated
May 19, 2024 - Jupyter Notebook
An Easy-to-use Knowledge Editing Framework for LLMs.
Awesome Machine Unlearning (A Survey of Machine Unlearning)
[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
[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
The official implementation of the 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.
Code for implementation of Unlearning Scanner Bias for MRI Harmonisation
Continual Forgetting for Pre-trained Vision Models (CVPR 2024)
A resource repository for machine unlearning in large language models
Pytorch implementation of backdoor unlearning.
Implementation for MICCAI DART paper: 'Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification'
"Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu
Repo on unlearning in FL. FYP22002@HKUCS.
Implementation for ICML 2022 paper: 'Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification'
Official implementation of "Deeper Understanding of Black-box Predictions via Generalized Influence Functions".
Official Website of https://github.com/tamlhp/awesome-machine-unlearning
Unlearning Java, with Spring boot. AmigosCode https://youtu.be/9SGDpanrc8U
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