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Gender Bias in Machine Translation

arXiv 2104.06001 ↗First posted 13 Apr 2021cs.CLcited by 116

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Abstract (arXiv)

Machine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, elaborating and communicating information. However, it can suffer from biases that harm users and society at large. As a relatively new field of inquiry, gender bias in MT still lacks internal cohesion, which advocates for a unified framework to ease future research. To this end, we: i) critically review current conceptualizations of bias in light of theoretical insights from related disciplines, ii) summarize previous analyses aimed at assessing gender bias in MT, iii) discuss the mitigating strategies proposed so far, and iv) point toward potential directions for future work.

Key facts. Cited by 116 papers in the map (data through 7 Oct 2026). Builds on 68 of its 261 references that are in the map. First posted on arXiv 13 Apr 2021.

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68 of 261 references.

References · 68

  1. 2020Shortcut Learning in Deep Neural Networkscited by 1,928
  2. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  3. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  4. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  5. 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
  6. 2019Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inferencecited by 864
  7. 2018Gender Bias in Coreference Resolution: Evaluation and Debiasing Methodscited by 657
  8. 2018Gender Bias in Coreference Resolutioncited by 438
  9. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  10. 2019Social Bias Frames: Reasoning about Social and Power Implications of Languagecited by 377
  11. 2019Measurement and Fairnesscited by 299
  12. 2019Mitigating Gender Bias in Natural Language Processing: Literature Reviewcited by 287
38 more
  1. 2019Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Themcited by 268
  2. 2020Data and its (dis)contents: A survey of dataset development and use in machine learning researchcited by 259
  3. 2019Evaluating Gender Bias in Machine Translationcited by 247
  4. 2018Women also Snowboard: Overcoming Bias in Captioning Modelscited by 236
  5. 2018Gender Bias in Neural Natural Language Processingcited by 210
  6. 2019Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphologycited by 200
  7. 2019Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasetscited by 173
  8. 2018Learning Gender-Neutral Word Embeddingscited by 169
  9. 2020Intrinsic Bias Metrics Do Not Correlate with Application Biascited by 148
  10. 2019Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddingscited by 146
  11. 2019Towards Debiasing Fact Verification Modelscited by 143
  12. 2020Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructurecited by 138
  13. 2019Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overviewcited by 137
  14. 2019End-to-End Bias Mitigation by Modelling Biases in Corporacited by 127
  15. 2018Assessing Gender Bias in Machine Translation -- A Case Study with Google Translatecited by 121
  16. 2019Getting Gender Right in Neural Machine Translationcited by 98
  17. 2020Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problemcited by 86
  18. 2019Toward Gender-Inclusive Coreference Resolutioncited by 84
  19. 2020Multi-Dimensional Gender Bias Classificationcited by 80
  20. 2018Towards Robust and Privacy-preserving Text Representationscited by 75
  21. 2021Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translationcited by 70
  22. 2019Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniquescited by 65
  23. 2019On Measuring Gender Bias in Translation of Gender-neutral Pronounscited by 59
  24. 2020Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpuscited by 57
  25. 2020Gender Bias in Multilingual Embeddings and Cross-Lingual Transfercited by 55
  26. 2016Personalized Machine Translation: Preserving Original Author Traitscited by 47
  27. 2019Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translationcited by 45
  28. 2019When and Why is Document-level Context Useful in Neural Machine Translation?cited by 45
  29. 2021They, Them, Theirs: Rewriting with Gender-Neutral Englishcited by 44
  30. 2020Mitigating Gender Bias in Machine Translation with Target Gender Annotationscited by 42
  31. 2019Examining Gender Bias in Languages with Grammatical Gendercited by 40
  32. 2020Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make Itcited by 40
  33. 2016How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairscited by 39
  34. 2021Disembodied Machine Learning: On the Illusion of Objectivity in NLPcited by 37
  35. 2015Computational Sociolinguistics: A Surveycited by 35
  36. 2019On the Linguistic Representational Power of Neural Machine Translation Modelscited by 34
  37. 2015It's a Man's Wikipedia? Assessing Gender Inequality in an Online Encyclopediacited by 30
  38. 2019Distilling Translations with Visual Awarenesscited by 30

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 9; 2023: 32; 2024: 32; 2025: 24; 2026: 9.

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  1. 2021Societal Biases in Language Generation: Progress and Challengescited by 201
  2. 2023Accelerating Transformer Inference for Translation via Parallel Decodingcited by 123
  3. 2021A Survey on Gender Bias in Natural Language Processingcited by 89
  4. 2021Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metricscited by 83
  5. 2023Inseq: An Interpretability Toolkit for Sequence Generation Modelscited by 78
  6. 2024INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledgecited by 78
  7. 2024The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harmcited by 67
  8. 2022Theories of "Gender" in NLP Bias Researchcited by 62
  9. 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
  10. 2024IrokoBench: A New Benchmark for African Languages in the Age of Large Language Modelscited by 43
  11. 2025The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating Itcited by 42
  12. 2024Angry Men, Sad Women: Large Language Models Reflect Gendered Stereotypes in Emotion Attributioncited by 39
38 more
  1. 2022MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translationcited by 38
  2. 2022Representation Bias in Data: A Survey on Identification and Resolution Techniquescited by 37
  3. 2023Lost in Translation: Large Language Models in Non-English Content Analysiscited by 34
  4. 2024IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Contextcited by 32
  5. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 27
  6. 2023Survey of Social Bias in Vision-Language Modelscited by 26
  7. 2024Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Artcited by 26
  8. 2023Debiasing Algorithm through Model Adaptationcited by 24
  9. 2021Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue modelscited by 23
  10. 2022Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translationcited by 23
  11. 2023Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scalecited by 23
  12. 2023Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challengescited by 22
  13. 2023Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpuscited by 20
  14. 2021Evaluating Gender Bias in Hindi-English Machine Translationcited by 19
  15. 2023What about em? How Commercial Machine Translation Fails to Handle (Neo-)Pronounscited by 19
  16. 2023A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translationcited by 19
  17. 2024What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Studycited by 15
  18. 2021The Arabic Parallel Gender Corpus 2.0: Extensions and Analysescited by 12
  19. 2023Women Are Beautiful, Men Are Leaders: Gender Stereotypes in Machine Translation and Language Modelingcited by 12
  20. 2024A Prompt Response to the Demand for Automatic Gender-Neutral Translationcited by 12
  21. 2024The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMscited by 12
  22. 2021How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translationcited by 11
  23. 2024ALaRM: Align Language Models via Hierarchical Rewards Modelingcited by 11
  24. 2023Target-Agnostic Gender-Aware Contrastive Learning for Mitigating Bias in Multilingual Machine Translationcited by 10
  25. 2024Watching the Watchers: Exposing Gender Disparities in Machine Translation Quality Estimationcited by 10
  26. 2025The Multilingual Divide and Its Impact on Global AI Safetycited by 10
  27. 2023In the Name of Fairness: Assessing the Bias in Clinical Record De-identificationcited by 9
  28. 2022User-Centric Gender Rewritingcited by 7
  29. 2023Gender, names and other mysteries: Towards the ambiguous for gender-inclusive translationcited by 7
  30. 2023Exploring the Impact of Training Data Distribution and Subword Tokenization on Gender Bias in Machine Translationcited by 7
  31. 2024Enhancing Gender-Inclusive Machine Translation with Neomorphemes and Large Language Modelscited by 7
  32. 2025Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine Translationcited by 7
  33. 2025What Is The Political Content in LLMs' Pre- and Post-Training Data?cited by 7
  34. 2023Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translationcited by 6
  35. 2023Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INEScited by 6
  36. 2024Whose wife is it anyway? Assessing bias against same-gender relationships in machine translationcited by 6
  37. 2024SAGED: A Holistic Bias-Benchmarking Pipeline for Language Models with Customisable Fairness Calibrationcited by 6
  38. 2025An Interdisciplinary Approach to Human-Centered Machine Translationcited by 6

50 most cited of 116 All 116 (JSON)