Preprint
Aug 2026
Are LLM-Enhanced GNNs Privacy-Safe?
A systematic evaluation of privacy risks in LLM-enhanced GNNs through a unified framework consisting of five stages and reveals that semantic enrichment amplifies link-, label-, and membership-related signals in the embedding space, making them more exploitable by inference attacks.
Longzhu He, Zekun Wen, Chaozhuo Li et al.
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