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Articles by Vincenzo Marco
Computer Science > Machine Learning
Graph Neural Networks (GNNs) can solve prediction tasks by unintentionally exploiting shortcuts---that is, edges, nodes, and features that correlate with but are not causal for the prediction---which compromise their reliability in out-of-distribution tasks. We introduce XIGL, an architecture-agnostic human-in-the-loop strategy for removing such shortcuts from GNNs. Our key insight is twofold.
Computer Science > Artificial Intelligence
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[2507.13305] Boosting Team Modeling through Tempo-Relational Representation Learning
[Submitted on 17 Jul 2025] Title:Boosting Team Modeling through Tempo-Relational Representation Learning View a PDF of the paper titled Boosting Team Modeling through Tempo-Relational Representation Learning, by Vincenzo Marco De Luca and 2 other authors View PDF HTML (experimental) Abstract:Team modeling remains a fundamental challenge at the intersection of Artificial Intelligence and the Social Sciences.
xAI-Drop: Don't Use What You Cannot Explain
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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