Good, but not always fair: An evaluation of gender bias for three commercial machine translation systems

SA Piazzolla, B Savoldi, L Bentivogli - arXiv preprint arXiv:2306.05882, 2023 - arxiv.org
Machine Translation (MT) continues to make significant strides in quality and is increasingly
adopted on a larger scale. Consequently, analyses have been redirected to more nuanced …

[图书][B] The social impact of automating translation: An ethics of care perspective on machine translation

E Monzó-Nebot, V Tasa-Fuster - 2024 - books.google.com
This collection critically examines the practical impacts of machine translation (MT) through
the lens of an ethics of care. It addresses the ideological issues in MT development linked to …

Quantifying Gender Bias in Arabic Pre-trained Language Models

W Alrajhi, H Al-Khalifa, AM Al-Salman - IEEE Access, 2024 - ieeexplore.ieee.org
The current renaissance in the development of Arabic Pre-trained Language models
(APLMs) has yielded significant advancement across many fields. Nevertheless, no study …

[PDF][PDF] Correcting biased translations with the Fairslator API

M Měchura - Translating and the Computer 45, 2023 - tradulex.com
This paper introduces the Fairslator API, a software solution for gender rewriting and form-
ofaddress rewriting of translations. Starting with a review of bias (including but not limited to …