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2024
B. Muscato, Mala, C. Sree, Manerba, M. Marchiori, Gezici, G., and Giannotti, F., “An Overview of Recent Approaches to Enable Diversity in Large Language Models through Aligning with Human Perspectives”, in Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024, Torino, Italia, 2024.
B. Muscato, Mala, C. Sree, Manerba, M. Marchiori, Gezici, G., and Giannotti, F., “An Overview of Recent Approaches to Enable Diversity in Large Language Models through Aligning with Human Perspectives”, in Proceedings of the 3rd Workshop on Perspectivist Approaches to NLP (NLPerspectives) @ LREC-COLING 2024, Torino, Italia, 2024.
2023
F. Naretto, Monreale, A., and Giannotti, F., “Evaluating the Privacy Exposure of Interpretable Global and Local Explainers”, in Submitted at Journal of Artificial Intelligence and Law, 2023.
L. Corbucci, Guidotti, R., and Monreale, A., “Explaining Black-Boxes in Federated Learning”, in Explainable Artificial Intelligence, Cham, 2023.
D. Gambetta, Mauro, G., and Pappalardo, L., “Mobility Constraints in Segregation Models”, Scientific Reports, vol. 13, p. 12087, 2023.
2022
F. Bodria, Rinzivillo, S., Fadda, D., Guidotti, R., Giannotti, F., and Pedreschi, D., “Explaining Black Box with visual exploration of Latent Space”, EuroVis–Short Papers, 2022.
F. Bodria, Rinzivillo, S., Fadda, D., Guidotti, R., Giannotti, F., and Pedreschi, D., “Explaining Black Box with visual exploration of Latent Space”, EuroVis–Short Papers, 2022.
A. Fedele, Guidotti, R., and Pedreschi, D., “Explaining Siamese Networks in Few-Shot Learning for Audio Data”, in Discovery Science - 25th International Conference, DS 2022, Montpellier, France, October 10-12, 2022, Proceedings, 2022.
A. Rita Nogueira, Pugnana, A., Ruggieri, S., Pedreschi, D., and Gama, J., “Methods and tools for causal discovery and causal inference”, WIREs Data Mining Knowl. Discov., vol. 12, 2022.
M. Fontana, Naretto, F., Monreale, A., and Giannotti, F., “Monitoring Fairness in HOLDA”, in HHAI 2022: Augmenting Human Intellect - Proceedings of the First International Conference on Hybrid Human-Artificial Intelligence, Amsterdam, The Netherlands, 13-17 June 2022, 2022.
R. Trasarti, Grossi, V., Natilli, M., and Rapisarda, B., “SoBigData++: European Integrated Infrastructure for Social Mining and Big Data Analytics.”, 30th Italian Symposium on Advanced Database Systems (SEBD – Sistemi Evoluti per Basi di Dati). Tirrenia, Pisa, 2022.
R. Guidotti, Monreale, A., Ruggieri, S., Naretto, F., Turini, F., Pedreschi, D., and Giannotti, F., “Stable and actionable explanations of black-box models through factual and counterfactual rules”, Data Mining and Knowledge Discovery, 2022.
R. Guidotti, Monreale, A., Ruggieri, S., Naretto, F., Turini, F., Pedreschi, D., and Giannotti, F., “Stable and actionable explanations of black-box models through factual and counterfactual rules”, Data Mining and Knowledge Discovery, 2022.
2021
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
F. Giannotti, Naretto, F., and Bodria, F., “Explainable for Trustworthy AI”, in Human-Centered Artificial Intelligence - Advanced Lectures, 18th European Advanced Course on AI, ACAI 2021, Berlin, Germany, October 11-15, 2021, extended and improved lecture notes, 2021.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
L. Pappalardo, Grossi, V., and Pedreschi, D., “Introduction to the special issue on social mining and big data ecosystem for open, responsible data science”, 2021.
2020
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., “Analysis and Visualization of Performance Indicators in University Admission Tests”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., “Analysis and Visualization of Performance Indicators in University Admission Tests”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.
B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.

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