benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
Organizes papers by tier-1 conference venues spanning network science, NLP, data mining, and AI—enabling researchers to track fraud detection advances across methodological paradigms. Papers emphasize graph neural networks, temporal-spatial modeling, and semi-supervised approaches, with recent work addressing adversarial robustness and limited-label scenarios. Includes direct links to implementations and preprints, facilitating reproducibility across complementary collections on graph classification and community detection.
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Jan 05, 2026
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