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Open access Aug 2026

Learning with Blacklists on Graphs via Prototype-Guided Dual-Frequency Filtering

Graph-based fraud detection plays a critical role in identifying anomalous accounts and preventing financial losses in real-world systems, where graphs often contain millions of nodes but only a limited number of blacklist labels are available. Existing graph neural network approaches typically rely on full-graph messa...

Hang Yu, Zheng-Yang Liu · 0 citations
#machine learning Preprint Sep 2026

SAGE-Loop: Reliable Closed-Loop LLM-Driven AutoML with Trial-and-Correction and Adaptive Ensembling

Automated machine learning (AutoML) is reshaping data-driven science and industrial practice, and as large language models are introduced into AutoML, pipeline reliability becomes as important as automation efficiency. However, existing AutoML still struggles to realize instant feedback and adaptive optimization during...

Jun-Quan Gu, Shi-Bo Cui, Xiang-Feng Luo et al. · 0 citations

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