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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…
cs.AI2026
Engineering AI Agents for Clinical Workflows: A Case Study in Architecture,MLOps, and Governance
Cláudio Lúcio do Val Lopes, João Marcus Pitta, Fabiano Belém +2
The integration of Artificial Intelligence (AI) into clinical settings presents a software engineering challenge, demanding a shift from isolated models to robust, governable, and…