4 papers
MARCO: The Radioactive Watermark for Protein Generative Models
Huajie Chen, Xin Guo, Yuchen Shi +7
Protein Generative Models (PGMs) have revolutionized structural biology by enabling the design of complex 3D protein structures from sequence data. However, this breakthrough intro…
One Framework for All: Cross-Modal Membership Inference for Generative Models
Dayong Ye, Tainqing Zhu, Kun Gao +6
Large generative models across text-to-text, text-to-image, and image-to-text modalities have been shown to pose significant privacy risks. One fundamental threat is membership inf…
Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning
Dayong Ye, Tianqing Zhu, Jiayang Li +5
Duplication is a prevalent issue within datasets. Existing research has demonstrated that the presence of duplicated data in training datasets can significantly influence both mode…
Reinforcement Unlearning
Dayong Ye, Tianqing Zhu, Congcong Zhu +6
Machine unlearning refers to the process of mitigating the influence of specific training data on machine learning models based on removal requests from data owners. However, one i…