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Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Recent years have seen an increasing need for gender-neutral and inclusive language. Within the field of NLP, there are various mono-and bilingual use cases where gender inclusive language is appropriate, if not preferred due to ambiguity or uncertainty in terms of the gender of referents. In this work, we present a rulebased and a neural approach to gender-neutral rewriting for English along with manually curated synthetic data (WinoBias+) and natural data (OpenSubtitles and Reddit)doi:10.18653/v1/2021.emnlp-main.704 fatcat:fgz6raqp6ffh3mjajjw5qragoq