This article investigates the unwanted bias in pretrained vision-and-language (V&L) models, with a focus on gender bias. The authors quantified bias amplification in pretraining and after fine-tuning on three families…
Continue readingThe paper titled ‘Fair Canonical Correlation Analysis’ focuses on the issue of fairness and bias in Canonical Correlation Analysis (CCA). The authors present a framework that aims to reduce unfairness…
Continue readingThis paper presents a novel framework, Concept Influence for Fairness (CIF), to understand and address the issue of unfairness in machine learning models. The authors propose a method to quantify…
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