{"total":13,"rows":[{"id":"2306.06108","title":"Demystifying Fraudulent Transactions and Illicit Nodes in the Bitcoin Network for Financial Forensics","created":"2023-05-25","cited_by_count":19,"area":null},{"id":"2402.06330","title":"Continual Learning on Graphs: A Survey","created":"2024-02-09","cited_by_count":12,"area":null},{"id":"2307.13499","title":"Finding Money Launderers Using Heterogeneous Graph Neural Networks","created":"2023-07-25","cited_by_count":5,"area":null},{"id":"2404.18251","title":"Machine Learning for Blockchain Data Analysis: Progress and Opportunities","created":"2024-04-28","cited_by_count":2,"area":null},{"id":"2311.13731","title":"A Survey of Blockchain, Artificial Intelligence, and Edge Computing for Web 3.0","created":"2023-11-22","cited_by_count":1,"area":null},{"id":"2503.10058","title":"Deep Learning Approaches for Anti-Money Laundering on Mobile Transactions: Review, Framework, and Directions","created":"2025-03-13","cited_by_count":1,"area":null},{"id":"2503.24259","title":"Advances in Continual Graph Learning for Anti-Money Laundering Systems: A Comprehensive Review","created":"2025-03-31","cited_by_count":1,"area":null},{"id":"2603.14592","title":"A Multi-Scale Graph Learning Framework with Temporal Consistency Constraints for Financial Fraud Detection in Transaction Networks under Non-Stationary Conditions","created":"2026-03-15","cited_by_count":1,"area":null},{"id":"2506.04292","title":"GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2603.16080","title":"A Depth-Aware Comparative Study of Euclidean and Hyperbolic Graph Neural Networks on Bitcoin Transaction Systems","created":"2026-03-17","cited_by_count":0,"area":null},{"id":"2604.19514","title":"When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift","created":"2026-04-21","cited_by_count":0,"area":null},{"id":"2605.11029","title":"FragBench: Cross-Session Attacks Hidden in Benign-Looking Fragments","created":"2026-05-10","cited_by_count":0,"area":null},{"id":"2609.03036","title":"Population-Calibrated Graph Screening at 835-Million-Address Scale, with Label-Free Transfer to New Chains","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}