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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Jing Zhang

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Sep 2026

SAGAD: A Graph Foundation Model for Generalist Few-Shot Anomaly Detection via Fine-Grained Disentanglement.

This work proposes structural-anomaly perception and attribute-anomaly perception GAD (SAGAD), a novel GAD-oriented GFM tailored for fine-grained anomaly perception and achieves highly competitive performance compared to state-of-the-art methods under the GAD-oriented GFMs paradigm in few-shot scenarios.

Ming-Yu Wang, Wan-Xiang Zhang, Jing Zhang · 0 citations
Conference Open access Sep 2026

FedFINFO: A General Full-Informativeness Federated Graph Learning from Open Cross-Domain Data

This work proposes a counterfactual multi-view framework to explicitly learn a structure masker for extracting consensus subgraphs and proposes a history-aware adaptive multi-channel aggregation mechanism to enable dynamic and personalized sharing driven by channel similarity while preventing collaborative oscillation.

Wan Zhang, Xiao-Qian Jiang, Ye Wang et al. · 0 citations

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