Enhancing Gender-Inclusive Machine Translation with Neomorphemes and Large Language Models

A Piergentili, B Savoldi, M Negri… - arXiv preprint arXiv …, 2024 - arxiv.org
Machine translation (MT) models are known to suffer from gender bias, especially when
translating into languages with extensive gendered morphology. Accordingly, they still fall …

The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs

A Sant, C Escolano, A Mash, FDL Fornaciari… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper studies gender bias in machine translation through the lens of Large Language
Models (LLMs). Four widely-used test sets are employed to benchmark various base LLMs …

[PDF][PDF] Automatic detection of (potential) factors in the source text leading to gender bias in machine translation

J Hackenbuchner, A Tezcan… - Proceedings of the 24th …, 2024 - backoffice.biblio.ugent.be
This research project aims to develop a comprehensive methodology to help make machine
translation (MT) systems more gender-inclusive for society. The goal is the creation of a …

You Shall Know a Word's Gender by the Company it Keeps: Comparing the Role of Context in Human Gender Assumptions with MT

J Hackenbuchner, J Daems, A Tezcan… - Proceedings of the …, 2024 - aclanthology.org
In this paper, we analyse to what extent machine translation (MT) systems and humans base
their gender translations and associations on role names and on stereotypicality in the …

[PDF][PDF] Innovations and Challenges in Neural Machine Translation: A Review

M Ashraf - researchgate.net
Neural Machine Translation NMT has revolutionized language translation through the use of
deep learning techniques that offer greater accuracy and contextual understanding …