ReGAP formulates follow-up question generation as a sequential intervention planning problem, and uses Monte Carlo Tree Search to compare candidate intervention strategies over future dialogue trajectories, and further incorporates experience priors to improve planning efficiency and stability.
Wanqiang Wang, Long-Zhu He, Peng-Peng Zhou et al.· ACM Transactions on Intellig...· 0 citations
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.
Long-Zhu He, Ze-Kun Wen, Chao-Zhuo Li et al.· 0 citations
This survey presents the first comprehensive and systematic review of Differentially Private Graph Learning (DPGL), and organizes existing DPGL methods into four categories based on the granularity of privacy protection, namely node-level, edge-level, graph-level, and node-level.
Li Sun, Long-Zhu He, Ming Li et al.· Transactions on Graph Intell...· 1 citation
PPGNN, a personalized differentially private framework for decentralized graph data, enables user-specific privacy budgets during local perturbation while preserving analytical utility in decentralized graph learning scenarios.
Longzhu He, Peng Tang, Chaozhuo Li et al.· IEEE Transactions on Knowled...· 0 citations
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