2 papers
cs.LG2024
The Explabox: Model-Agnostic Machine Learning Transparency & Analysis
Marcel Robeer, Michiel Bron, Elize Herrewijnen +2
We present the Explabox: an open-source toolkit for transparent and responsible machine learning (ML) model development and usage. Explabox aids in achieving explainable, fair and…
cs.CL2023
Contrast Is All You Need
Burak Kilic, Florix Bex, Albert Gatt
In this study, we analyze data-scarce classification scenarios, where available labeled legal data is small and imbalanced, potentially hurting the quality of the results. We focus…