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cs.LG2026
Rethinking Fairness Metrics for Multi-Class and Multi-Group Assessment: Not Everything is Binary
Matteo Grazioso, Fabio Naccarella, Chiara Gallese +1
Artificial Intelligence, and Machine Learning in general, is becoming pervasive across all domains and disciplines. By means of this data-driven approach, algorithms can learns com…
cs.CY2026
Advancing Trustworthy AI in Healthcare Through Meta-Research: Results of an Interdisciplinary Design-Thinking Workshop
Valerie Bürger, Marlie Besouw, Jana Fehr +26
Meta-research and Trustworthy AI (TAI) share common goals, namely improving evidence, robustness, and transparency, yet there is very little interplay between the two fields. To in…