GeNRe: A French Gender-Neutral Rewriting System Using Collective Nouns
Not on the map. Why?
Abstract (arXiv)
A significant portion of the textual data used in the field of Natural Language Processing (NLP) exhibits gender biases, particularly due to the use of masculine generics (masculine words that are supposed to refer to mixed groups of men and women), which can perpetuate and amplify stereotypes. Gender rewriting, an NLP task that involves automatically detecting and replacing gendered forms with neutral or opposite forms (e.g., from masculine to feminine), can be employed to mitigate these biases. While such systems have been developed in a number of languages (English, Arabic, Portuguese, German, French), automatic use of gender neutralization techniques (as opposed to inclusive or gender-switching techniques) has only been studied for English. This paper presents GeNRe, the very first French gender-neutral rewriting system using collective nouns, which are gender-fixed in French. We introduce a rule-based system (RBS) tailored for the French language alongside two fine-tuned language models trained on data generated by our RBS. We also explore the use of instruct-based models to enhance the performance of our other systems and find that Claude 3 Opus combined with our dictionary achieves results close to our RBS. Through this contribution, we hope to promote the advancement of gender bias mitigation techniques in NLP for French.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 23 of its 59 references that are in the map. First posted on arXiv 29 May 2025.
Builds on
23 of 59 references.
References · 23
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
- 2018A Call for Clarity in Reporting BLEU Scorescited by 1,799
- 2024A Survey on LLM-as-a-Judgecited by 1,423
- 2018Gender Bias in Coreference Resolution: Evaluation and Debiasing Methodscited by 659
- 2020Beyond English-Centric Multilingual Machine Translationcited by 561
- 2019CamemBERT: a Tasty French Language Modelcited by 368
- 2019Mitigating Gender Bias in Natural Language Processing: Literature Reviewcited by 287
- 2018Gender Bias in Neural Natural Language Processingcited by 211
11 more
- 2021Gender Bias in Machine Translationcited by 117
- 2021A Survey on Gender Bias in Natural Language Processingcited by 89
- 2021NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternativescited by 46
- 2021They, Them, Theirs: Rewriting with Gender-Neutral Englishcited by 44
- 2021Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decodingcited by 23
- 2023Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpuscited by 20
- 2024From 'Showgirls' to 'Performers': Fine-tuning with Gender-inclusive Language for Bias Reduction in LLMscited by 15
- 2025FairTranslate: An English-French Dataset for Gender Bias Evaluation in Machine Translation by Overcoming Gender Binaritycited by 5
- 2022INCLUSIFY: A benchmark and a model for gender-inclusive Germancited by 2
- 2022Screening Gender Transfer in Neural Machine Translationcited by 1
- 2022The Shared Task on Gender Rewritingcited by 1
Built on by
Citing papers per year: 2025: 1.
1 paper.