Overview of the Shared Task on Machine Translation Gender Bias Evaluation with Multilingual Holistic Bias

Abstract

We describe the details of the Shared Task of the 5th ACL Workshop on Gender Bias in Natural Language Processing (GeBNLP 2024). The task uses dataset to investigate the quality of Machine Translation systems on a particular case of gender robustness. We report baseline results as well as the results of the first participants. The shared task will be permanently available in the Dynabench platform.

Publication
Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP) at ACL 2024