2 papers
cs.LG2026
Denoising-Aware Inversion: Revealing Privacy Risks in Noise-Protected Text Embeddings
Yubo Wang, Shujie Cui, James Bailey +5
Dense text embeddings are widely used in data mining, retrieval, and downstream machine learning systems due to their compact and semantically rich representations, but recent embe…
cs.IR2025
Privacy Risks of LLM-Empowered Recommender Systems: An Inversion Attack Perspective
Yubo Wang, Min Tang, Nuo Shen +2
The large language model (LLM) powered recommendation paradigm has been proposed to address the limitations of traditional recommender systems, which often struggle to handle cold…