[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.

A resource repository for machine unlearning in large language models

Papers related to Machine/ Federated Unlearning in all top venues

[EMNLP 2024 Findings] To Forget or Not? Towards Practical Knowledge Unlearning for 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

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.

Official implementation of NeurIPS'24 paper "Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models". This work adversarially unlearns the text encoder to enhance the robustness of unlearned DMs against adversarial prompt attacks and achieves a better balance between unlearning performance and image generation

Official Code of Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers (AAAI 2024)

Experiments for our CLEAR benchmark of unlearning methods in a multimodal setup

ConceptVectors Benchmark and Code for the paper "Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces"

[ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu

RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models. NeurIPS 2024

[ACL 2024] Code and data for "Machine Unlearning of Pre-trained Large Language Models"

[NeurIPS 2024] Large Language Model Unlearning via Embedding-Corrupted Prompts

Continual Forgetting for Pre-trained Vision Models (CVPR 2024)

Awesome Machine Unlearning (A Survey of Machine Unlearning)

Coursework and projects for ML course, including theoretical homework solutions/problems, final solution/problems and the project of the course

Demystifying Verbatim Memorization in Large Language Models

Official Website of https://github.com/tamlhp/awesome-machine-unlearning