1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026
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…
cs.CY2024
Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage
Hengzhu Liu, Tianqing Zhu, Lefeng Zhang +1
With the extensive use of machine learning technologies, data providers encounter increasing privacy risks. Recent legislation, such as GDPR, obligates organizations to remove requ…
cs.CR2024★ 1 cited
A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
Hengzhu Liu, Ping Xiong, Tianqing Zhu +1
The explosive growth of machine learning has made it a critical infrastructure in the era of artificial intelligence. The extensive use of data poses a significant threat to indivi…