1 citations · 2 across the 7 of their papers we have counts for
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Membership Inference Attacks on Recommender System: A Survey
Jiajie He, Xintong Chen, Xinyang Fang +4
Recommender systems (RecSys) have been widely applied to various applications, including E-commerce, finance, healthcare, social media and have become increasingly influential in s…
Auditing Approximate Machine Unlearning for Differentially Private Models
Yuechun Gu, Jiajie He, Keke Chen
Approximate machine unlearning aims to remove the effect of specific data from trained models to ensure individuals' privacy. Existing methods focus on the removed records and assu…
Membership Inference Attacks on In-Context Examples in LLM-based Recommender Systems
Jiajie He, Min-Chun Chen, Xintong Chen +3
Large language models (LLMs) based recommender systems (RecSys) can adapt flexibly across different domains. It uses in-context learning (ICL), i.e., prompts, including sensitive h…
RecPS: Privacy Risk Scoring for Recommender Systems
Jiajie He, Yuechun Gu, Keke Chen
Recommender systems (RecSys) have become an essential component of many web applications. The core of the system is a recommendation model trained on highly sensitive user-item int…