arXiv AI
Graph-Transformer Fraud Detection with Self-Supervised Pretraining and Conformal Risk Control
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Hybrid LSTM-Graph Neural Framework for Robust Financial Fraud Detection and Adversarial Resilience
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Jun 29
Beyond Sparse Supervision: Diffusion-Guided Learning for Few-Shot Graph Fraud Detection
arXiv:2606. 28134v1 Announce Type: cross Abstract: Graph-based fraud detection is essential for safeguarding large-scale transaction systems, where undetected anomalies may lead to substantial financial losses and security risks.
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Jul 10
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Jul 22
Toward Auditable Fraud Detection: Combining Graph Features, Model Explanations, and Agentic Case Investigation
arXiv:2607. 19266v1 Announce Type: cross Abstract: Fraud detection systems must scale with rising transaction volume while remaining explainable and reviewable.
arXiv AI
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SAGE: An LLM-driven Self Reflective Agentic Framework for Fraud Detection
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arXiv AI
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Fraud is Not Just Rarity: A Causal Prototype Attention Approach to Realistic Synthetic Oversampling
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