4 papers · 1 filter
CUFG: Curriculum Unlearning Guided by the Forgetting Gradient
Jiaxing Miao, Liang Hu, Qi Zhang +2
As privacy and security take center stage in AI, machine unlearning, the ability to erase specific knowledge from models, has garnered increasing attention. However, existing metho…
COLUR: Confidence-Oriented Learning, Unlearning and Relearning with Noisy-Label Data for Model Restoration and Refinement
Zhihao Sui, Liang Hu, Jian Cao +3
Large deep learning models have achieved significant success in various tasks. However, the performance of a model can significantly degrade if it is needed to train on datasets wi…
Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy
Zhihao Sui, Liang Hu, Jian Cao +4
Machine Unlearning (MU) technology facilitates the removal of the influence of specific data instances from trained models on request. Despite rapid advancements in MU technology,…
CoSD: Collaborative Stance Detection with Contrastive Heterogeneous Topic Graph Learning
Yinghan Cheng, Qi Zhang, Chongyang Shi +3
Stance detection seeks to identify the viewpoints of individuals either in favor or against a given target or a controversial topic. Current advanced neural models for stance detec…