#graph-analysis News & Analysis

3 articles tagged with #graph-analysis. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AI × CryptoBullisharXiv – CS AI · 3d ago7/10

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Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection

Researchers propose TEMG-TTA, a novel machine learning framework combining temporal motif analysis with test-time adaptation to improve anomaly detection on blockchain networks. The approach addresses critical challenges in detecting evolving fraudulent transaction patterns and out-of-distribution anomalies, demonstrating 54.88% performance improvement over existing graph-based detection methods across five real-world datasets.

AINeutralarXiv – CS AI · Mar 37/109

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Property-Driven Evaluation of GNN Expressiveness at Scale: Datasets, Framework, and Study

Researchers developed a comprehensive evaluation framework for Graph Neural Networks (GNNs) using formal specification methods, creating 336 new datasets to test GNN expressiveness across 16 fundamental graph properties. The study reveals that no single pooling approach consistently performs well across all properties, with attention-based pooling excelling in generalization while second-order pooling provides better sensitivity.

AINeutralarXiv – CS AI · May 95/10

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From Token Lists to Graph Motifs: Weisfeiler-Lehman Analysis of Sparse Autoencoder Features

Researchers introduce a novel graph-based analysis method for sparse autoencoders (SAEs) in transformer models, using Weisfeiler-Lehman graph kernels to examine token co-occurrence patterns in SAE features. Applied to GPT-2 Small, this approach identifies structural motif families that traditional decoder weight analysis misses, revealing complementary insights into how neural networks organize semantic information.