Pietro Barbiero

Former Member
Publications
Pietro Barbiero, Mateo Espinosa Zarlenga, Francesco Giannini, Alberto Termine, Filippo Bonchi, Mateja Jamnik, Giuseppe Marra (2026). Actionable Interpretability Must Be Defined in Terms of Symmetries. CoRR.
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Dario Fenoglio, Arianna Casanova, Francesco De Santis, Mohan Li, Gabriele Dominici, Johannes Schneider, Martin Gjoreski, Marc Langheinrich, Pietro Barbiero, Giovanni de Felice (2026). Federated Concept-Based Models: Interpretable models with distributed supervision. CoRR.
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Nicola Debole, Pietro Barbiero, Francesco Giannini, Andrea Passerini, Stefano Teso, Emanuele Marconato (2026). If Concept Bottlenecks are the Question, are Foundation Models the Answer?. Mach. Learn..
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Giovanni de Felice, Riccardo D'Elia, Alberto Termine, Pietro Barbiero, Giuseppe Marra, Silvia Santini (2026). Interpretability in Deep Time Series Models Demands Semantic Alignment. CoRR.
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Francesco De Santis, Gabriele Ciravegna, Giovanni de Felice, Arianna Casanova, Francesco Giannini, Michelangelo Diligenti, Mateo Espinosa Zarlenga, Pietro Barbiero, Johannes Schneider, Danilo Giordano (2026). Mixture of Concept Bottleneck Experts. CoRR.
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Stefano Colamonaco, David Debot, Pietro Barbiero, Giuseppe Marra (2026). Prototype-Grounded Concept Models for Verifiable Concept Alignment. CoRR.
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Pietro Barbiero, Giovanni de Felice, Mateo Espinosa Zarlenga, Francesco Giannini, Filippo Bonchi, Mateja Jamnik, Giuseppe Marra, Ruggero Noris (2026). The Standard Interpretable Model: A general theory of interpretable machine learning to deductively design interpretable methods using Lagrangian mechanics. CoRR.
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Zoja Anzur, Klara Zinkovic, Junos Lukan, Pietro Barbiero, Gasper Slapnicar, Mohan Li, Martin Gjoreski, Maike E. Debus, Sebastijan Trojer, Mitja Lustrek, Marc Langheinrich (2025). A Review of Methods for Unobtrusive Measurement of Work-Related Well-Being. Mach. Learn. Knowl. Extr..
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Mohan Li, Martin Gjoreski, Pietro Barbiero, Gasper Slapnicar, Mitja Lustrek, Nicholas D. Lane, Marc Langheinrich (2025). A Survey on Federated Learning in Human Sensing. CoRR.
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Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero, Zohreh Shams, Mateja Jamnik (2025). Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts. Forty-second International Conference on Machine Learning, ICML 2025, Vancouver, BC, Canada, July 13-19, 2025.
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Mateo Espinosa Zarlenga, Gabriele Dominici, Pietro Barbiero, Zohreh Shams, Mateja Jamnik (2025). Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts. CoRR.
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Stefano Fioravanti, Francesco Giannini, Pietro Barbiero, Paolo Frazzetto, Roberto Confalonieri, Fabio Zanasi, Nicolò Navarin (2025). Categorical Explaining Functors: Ensuring Coherence in Logical Explanations. Proceedings of the 22nd International Conference on Principles of Knowledge Representation and Reasoning, KR 2025, Melbourne, Australia, November 11-17, 2025.
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Gabriele Dominici, Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich (2025). Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning. The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025.
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Giovanni de Felice, Arianna Casanova Flores, Francesco De Santis, Silvia Santini, Johannes Schneider, Pietro Barbiero, Alberto Termine (2025). Causally Reliable Concept Bottleneck Models. Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, NeurIPS 2025, San Diego, CA, USA, December 2-7, 2025 / Mexico City, Mexico, November 30 - December 5, 2025.
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Giovanni de Felice, Arianna Casanova Flores, Francesco De Santis, Silvia Santini, Johannes Schneider, Pietro Barbiero, Alberto Termine (2025). Causally Reliable Concept Bottleneck Models. CoRR.
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Gabriele Dominici, Pietro Barbiero, Francesco Giannini, Martin Gjoreski, Giuseppe Marra, Marc Langheinrich (2025). Counterfactual Concept Bottleneck Models. The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025.
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Andrea Pugnana, Riccardo Massidda, Francesco Giannini, Pietro Barbiero, Mateo Espinosa Zarlenga, Roberto Pellungrini, Gabriele Dominici, Fosca Giannotti, Davide Bacciu (2025). Deferring Concept Bottleneck Models: Learning to Defer Interventions to Inaccurate Experts. CoRR.
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Dario Fenoglio, Mohan Li, Pietro Barbiero, Nicholas D. Lane, Marc Langheinrich, Martin Gjoreski (2025). FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts. CoRR.
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Pietro Barbiero, Mateo Espinosa Zarlenga, Alberto Termine, Mateja Jamnik, Giuseppe Marra (2025). Foundations of Interpretable Models. CoRR.
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Nicola Debole, Pietro Barbiero, Francesco Giannini, Andrea Passerini, Stefano Teso, Emanuele Marconato (2025). If Concept Bottlenecks are the Question, are Foundation Models the Answer?. CoRR.
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David Debot, Pietro Barbiero, Gabriele Dominici, Giuseppe Marra (2025). Interpretable Hierarchical Concept Reasoning through Attention-Guided Graph Learning. CoRR.
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Rodrigo Castellano Ontiveros, Ehsan Bonabi Mobaraki, Francesco Giannini, Pietro Barbiero, Marco Gori, Michelangelo Diligenti (2025). Interpretable Link Prediction via Neural-Symbolic Reasoning. Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part II.
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Francesco De Santis, Philippe Bich, Gabriele Ciravegna, Pietro Barbiero, Danilo Giordano, Tania Cerquitelli (2025). Linearly-interpretable concept embedding models for text analysis. Mach. Learn..
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Stefano Fioravanti, Francesco Giannini, Paolo Frazzetto, Fabio Zanasi, Pietro Barbiero (2025). Logic Explanation of AI Classifiers by Categorical Explaining Functors. CoRR.
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Pietro Barbiero, Giuseppe Marra, Gabriele Ciravegna, David Debot, Francesco De Santis, Michelangelo Diligenti, Mateo Espinosa Zarlenga, Francesco Giannini (2025). Neural Interpretable Reasoning. CoRR.
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