🔗 Who cites «Automatic Gender Identification and Reinflection in Arabic»

42 papers of our library cite it (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · ← back to «Automatic Gender Identification and Reinflection in Arabic»

1. Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich MorphologyAnnual Meeting of the Association for Computational Linguistics (ACL)Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al.2019 · 376 citations
2. Gender Bias in Machine TranslationTransactions of the Association for Computational Linguistics (TACL)Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.2021 · 310 citations
3. Queens are Powerful too: Mitigating Gender Bias in Dialogue GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Emily Dinan, Angela Fan, Adina Williams, et al.2020 · 270 citations
4. Societal Biases in Language Generation: Progress and ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL)Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.2021 · 257 citations
5. Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine TranslationConference of the European Chapter of the Association for Computational Linguistics (EACL)Eva Vanmassenhove, Dimitar Shterionov, Matthew Gwilliam2021 · 162 citations
6. CIDAR: Culturally Relevant Instruction Dataset For ArabicFindings of the Association for Computational LinguisticsZaid Alyafeai, Khalid Almubarak, Ahmed Ashraf, et al.2024 · 30 citations
7. User-Centric Gender RewritingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bashar Alhafni, Nizar Habash, Houda Bouamor2022 · 29 citations
8. AraWEAT: Multidimensional Analysis of Biases in Arabic Word EmbeddingsArabic Natural Language Processing Workshop (WANLP)Anne Lauscher, Rafik Takieddin, Simone Paolo Ponzetto, et al.2020 · 26 citations
9. The Arabic Parallel Gender Corpus 2.0: Extensions and AnalysesLanguage Resources and Evaluation Conference (LREC)Bashar Alhafni, Nizar Habash, Houda Bouamor2022 · 21 citations
10. Weakly and Semi-Supervised Learning for Arabic Text Classification using Monodialectal Language ModelsArabic Natural Language Processing Workshop (WANLP)Reem AlYami, Rabah Al-Zaidy2022 · 11 citations
11. ArzEn-MultiGenre: An aligned parallel dataset of Egyptian Arabic song lyrics, novels, and subtitles, with English translationsarXiv:2508.01411 · Data in Brief, 54Rania Al-Sabbagh2024 · 9 citations
12. ArabGend: Gender Analysis and Inference on Arabic TwitterWorkshop on Noisy User-generated TextHamdy Mubarak, Shammur Absar Chowdhury, Firoj Alam2022 · 8 citations
13. Gender Bias Evaluation in Machine Translation for Amharic, Tigrigna, and Afaan OromooWorkshop on Gender-Inclusive Translation TechnologiesWalelign Sewunetie, Atnafu Tonja, Tadesse Belay, et al.2024 · 5 citations
14. The User-Aware Arabic Gender RewriterWorkshop on Gender-Inclusive Translation TechnologiesBashar Alhafni, Ossama Obeid, Nizar Habash2023 · 5 citations
15. Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only ArchitecturesLanguage Resources and Evaluation Conference (LREC)Chiara Manna, Hosein Mohebbi, Afra Alishahi, et al.2026 · 3 citations
16. The Shared Task on Gender RewritingArabic Natural Language Processing Workshop (WANLP)Bashar Alhafni, Nizar Habash, Houda Bouamor, et al.2022 · 3 citations
17. SERAG: Semantic Entity Retrieval from Arabic Knowledge GraphsArabic Natural Language Processing Workshop (WANLP)Saher Esmeir2021 · 3 citations
18. ArGAN: Arabic Gender, Ability, and Nationality Dataset for Evaluating Biases in Large Language ModelsWorkshop on Gender Bias in Natural Language ProcessingRanwa Aly, Yara Allam, Rana Gaber, et al.2025 · 1 citation
19. Rethinking Gender Annotation for Bias Evaluation in Machine Translation: Can LLMs Improve Reliability?Workshop on Gender-Inclusive Translation TechnologiesChiara Manna, Argentina Anna Rescigno, Eva Vanmassenhove2026

23 more papers of our library cite it; they have no page here yet.

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