3 papers
cs.LG2026
Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings
Inês Oliveira e Silva, Sérgio Jesus, Iker Perez +4
Shapley values are a cornerstone of explainable AI, yet their proliferation into competing formulations has created a fragmented landscape with little consensus on practical deploy…
cs.LG2024
Aequitas Flow: Streamlining Fair ML Experimentation
Sérgio Jesus, Pedro Saleiro, Inês Oliveira e Silva +5
Aequitas Flow is an open-source framework and toolkit for end-to-end Fair Machine Learning (ML) experimentation, and benchmarking in Python. This package fills integration gaps tha…
cs.LG2024
Fair-OBNC: Correcting Label Noise for Fairer Datasets
Inês Oliveira e Silva, Sérgio Jesus, Hugo Ferreira +4
Data used by automated decision-making systems, such as Machine Learning models, often reflects discriminatory behavior that occurred in the past. These biases in the training data…