This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …

Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …

Decision-making software mainly based on Machine Learning (ML) may contain fairness
issues (eg, providing favourable treatment to certain people rather than others based on …

This paper conducts fairness testing of automated pedestrian detection, a crucial but under-
explored issue in autonomous driving systems. We evaluate eight state-of-the-art deep …

Fairness has been a critical issue that affects the adoption of deep learning models in real
practice. To improve model fairness, many existing methods have been proposed and …

Fairness in artificial intelligence and machine learning (AI/ML) models is becoming critically
important, especially as decisions made by these systems impact diverse groups. In the …

Search-Based Software Engineering in the Era of Modern Software Systems Page 1 Search-Based
Software Engineering in the Era of Modern Software Systems Federica Sarro Department of …

With the increasing utilization of Machine Learning (ML) software in critical domains such as
employee hiring, college admission, and credit evaluation, ensuring fairness in the decision …

Machine translation is integral to international communication and extensively employed in
diverse human-related applications. Despite remarkable progress, fairness issues persist …

Efforts to mitigate bias and enhance fairness in the artificial intelligence (AI) community have
predominantly focused on technical solutions. While numerous reviews have addressed …