Author

Hui-Lin He

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#artificial intelligence Preprint Sep 2026

Behavior-Grounded Semantic Enrichment for Financial Fraud Modeling and Reasoning

A multi-agent semantic enrichment framework that generates interpretable financial semantics grounded in transaction behavior through role-specialized agents and consistency refinement is proposed and newly contribute a valuable multimodal financial fraud dataset, MS-FFSD, enriched with structured semantics and textual...

Lin-Bo Shao, Hui-Lin He, Yating Lou et al. · 0 citations

Conference Open access Sep 2026

Deep Reinforcement Learning Enhanced Semi-supervised Graph Neural Network for Credit Card Fraud Detection

This work proposes DRESS, a Deep Reinforcement Learning (DRL) Enhanced Semi-supervised GNN framework that employs a DRL agent to automatically capture and enhance feature-level risks, fusing them with graph-based structural risks and propagating via a gated temporal attention network for final prediction.

Hui-Lin He, Kun Zhu, Ze-Wen Hu et al. · Proceedings of the Thirty-Fi... · 0 citations