Semantic Pareto-DQN: Multi-Objective RL for Financial Anomaly Detection
A new research paper proposes Semantic Pareto-DQN, a multi-objective reinforcement learning framework that uses LLMs to encode transaction features into natural-language narratives for financial anomaly detection. The method aims to overcome class imbalance and 'fraud collapse' without distortive data resampling.
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