Author

Pietro Liò

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#artificial intelligence Preprint Sep 2026

ProtoGuide: Prototype-Driven Guidance for Class-Conditional Graph Generation

ProtoGuide is introduced, a post-hoc, backbone-agnostic framework that recovers an analogous mechanism for discrete diffusion models and raises macro classification accuracy and outperforms DiGress's built-in conditional training under the authors' configuration.

Salvatore Romano, Marco Grassia, Pietro Liò et al. · 0 citations

Review Open access Jul 2026

Differentially Private Graph Learning: A Survey

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