2 papers
cs.LG2026
Semantic Pareto-DQN: A Multi-Objective Reinforcement Learning Framework for Financial Anomaly Detection
Cláudio Lúcio do Val Lopes, Lucca Machado da Silva
Financial anomaly detection suffers from extreme class imbalance, causing traditional single-objective algorithms to exhibit ``fraud collapse'', defaulting to the majority class an…
cs.AI2026
Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation
Cláudio Lúcio Do Val Lopes, Lucca Machado da Silva, André de Oliveira Brandão
Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-objective models, including…