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Boosting Generalizable Fairness With Mahalanobis Distances Guided Boltzmann Exploratory Testing

Year: 2025

Type: article

Source: IEEE Transactions on Software Engineering

DOI: 10.1109/tse.2025.3581402

Authors: Kaixiang Dong, Peng Wu, Yanting Chen

Institutions: Chinese Academy of Sciences, Institute of Software, University of Chinese Academy of Sciences, State Key Laboratory of Computer Science

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Reduced inequalities

Open Access status: closed

Funder: National Key Research and Development Program of China

OpenAlex ID: W4411446586

FWCI:

Cites: 81

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Related to: 10