Making ML models fairer through explanations: the case of LimeOut

1 November 2020

Papers citing "Making ML models fairer through explanations: the case of LimeOut"

4 / 4 papers shown

Title
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration Vasiliki Papanikou Danae Pla Karidi E. Pitoura Emmanouil Panagiotou Eirini Ntoutsi 33 0 0 01 May 2025
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making Jakob Schoeffer Maria De-Arteaga Niklas Kuehl FaML 45 46 0 23 Sep 2022
Fairness of Machine Learning Algorithms in Demography I. Emmanuel E. Mitrofanova FaML 14 0 0 02 Feb 2022
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,090 0 24 Oct 2016