Author

Jianxin Li

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#artificial intelligence Feb 2026

Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts

This work proposes GAD-MoRE, a novel framework for zero-shot Generalizable Graph Anomaly Detection with a Mixture of Riemannian Experts architecture, which significantly outperforms state-of-the-art generalist GAD baselines in the zero-shot setting.

Xinyu Zhao, Qingyun Sun, Jiayi Luo et al. · arXiv.org · 0 citations

Jul 2026

DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation

DualG-MRAG is proposed, a Dual-tier framework that introduces a decoupled architecture comprising Macro-reasoning and Micro-matching Graphs for Multimodal RAG to suppress retrieval noise by isolating global structural reasoning from fine-grained evidence matching, and introduces a dynamic programming decoding mechanism that extracts explicit reasoning paths directly from the GNN's forward pass.

Jiachen Tao, Qingyun Sun, Haonan Yuan et al. · arXiv.org · 0 citations