3 papers
cs.CL2025
Direct Token Optimization: A Self-contained Approach to Large Language Model Unlearning
Hong kyu Lee, Ruixuan Liu, Li Xiong
Machine unlearning is an emerging technique that removes the influence of a subset of training data (forget set) from a model without full retraining, with applications including p…
cs.LG2025
Sharpness-Aware Parameter Selection for Machine Unlearning
Saber Malekmohammadi, Hong kyu Lee, Li Xiong
It often happens that some sensitive personal information, such as credit card numbers or passwords, are mistakenly incorporated in the training of machine learning models and need…
cs.LG2025
Node-level Contrastive Unlearning on Graph Neural Networks
Hong kyu Lee, Qiuchen Zhang, Carl Yang +1
Graph unlearning aims to remove a subset of graph entities (i.e. nodes and edges) from a graph neural network (GNN) trained on the graph. Unlike machine unlearning for models train…