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3 results for “Graph Neural Network”
Exploring Oversmoothing with Householder Matrices
A new graph neural network architecture called HouseGNN is proposed to mitigate oversmoothing in deep GNNs by using Householder reflectors and GroupSort to preserve node-wise Euclidean norms across layers.
Aug 14, 2026
Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey
A new arXiv preprint (2607.09666v1) publishes a comprehensive, taxonomy-driven survey of Graph Neural Network (GNN) applications across the full knowledge graph (KG) technology lifecycle — from construction to reasoning to applications — identifying gaps, strengths, limitations, and future research directions.
Jul 14, 2026
PRecG: Legal Precedent Retrieval with Graph Neural Networks and Rhetorical Role Segmentation
A new AI research paper proposes PRecG, a graph-based method for legal precedent retrieval that segments judgments by rhetorical role and builds knowledge graphs per segment to improve semantic matching.
Jul 13, 2026