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- Untying black boxes with clustering-based symbolic knowledge extraction (article in journal, 2024) — Federico Sabbatini, Roberta Calegari
- Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models (paper in proceedings, 2024) — Federico Sabbatini, Roberta Calegari
- On the Evaluation of the Symbolic Knowledge Extracted from Black Boxes (article in journal, 2024) — Federico Sabbatini, Roberta Calegari
- Symbolic Knowledge Comparison: Metrics and Methodologies for Multi-Agent Systems (paper in proceedings, 2024) — Federico Sabbatini, Christel Sirocchi, Roberta Calegari
- Towards a Unified Model for Symbolic Knowledge Extraction with Hypercube-Based Methods (article in journal, 2023) — Federico Sabbatini, Giovanni Ciatto, Roberta Calegari, Andrea Omicini
- Symbolic Knowledge-Extraction Evaluation Metrics: The FiRe Score (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- Bottom-Up and Top-Down Workflows for Hypercube- and Clustering-based Knowledge Extractors (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- A geometric framework for fairness (paper in proceedings, 2023) — Alessandro Maggio, Luca Giuliani, Roberta Calegari, Michele Lombardi, Michela Milano
- Explainable Clustering with CREAM (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- Unlocking Insights and Trust: The Value of Explainable Clustering Algorithms for Cognitive Agents (paper in proceedings, 2023) — Federico Sabbatini, Roberta Calegari
- Evaluation Metrics for Symbolic Knowledge Extracted from Machine Learning Black Boxes: A Discussion Paper (paper in proceedings, 2022) — Federico Sabbatini, Roberta Calegari
- Symbolic Knowledge Extraction from Opaque Machine Learning Predictors: GridREx & PEDRO (paper in proceedings, 2022) — Federico Sabbatini, Roberta Calegari