[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
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Updated
Sep 7, 2024 - Jupyter Notebook
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
Awesome Machine Unlearning (A Survey of Machine Unlearning)
A resource repository for machine unlearning in large language models
[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
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
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.
Continual Forgetting for Pre-trained Vision Models (CVPR 2024)
Code for implementation of Unlearning Scanner Bias for MRI Harmonisation
Official implementation of "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models"
Implementation for MICCAI DART paper: 'Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification'
Pytorch implementation of backdoor unlearning.
To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models
ConceptVectors Benchmark and Code for the paper "Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces"
"Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu
Implementation of paper 'Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference'
Repo on unlearning in FL. FYP22002@HKUCS.
Code for Large Language Model Unlearning via Embedding-Corrupted Prompts
Implementation for ICML 2022 paper: 'Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification'
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