mlsanityData to 7 Oct 2026

Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation

arXiv 2106.00169 ↗First posted 1 Jun 2021cs.CLcited by 28

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Abstract (arXiv)

Is bias amplified when neural machine translation (NMT) models are optimized for speed and evaluated on generic test sets using BLEU? We investigate architectures and techniques commonly used to speed up decoding in Transformer-based models, such as greedy search, quantization, average attention networks (AANs) and shallow decoder models and show their effect on gendered noun translation. We construct a new gender bias test set, SimpleGEN, based on gendered noun phrases in which there is a single, unambiguous, correct answer. While we find minimal overall BLEU degradation as we apply speed optimizations, we observe that gendered noun translation performance degrades at a much faster rate.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 22 of its 32 references that are in the map. First posted on arXiv 1 Jun 2021.

Builds on

22 of 32 references.

References · 22

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  2. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
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  4. 2019fairseq: A Fast, Extensible Toolkit for Sequence Modelingcited by 1,486
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  9. 2019Evaluating Gender Bias in Machine Translationcited by 247
  10. 2019Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphologycited by 200
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10 more
  1. 2020Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problemcited by 86
  2. 2019Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniquescited by 65
  3. 2020Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpuscited by 57
  4. 2020Mitigating Gender Bias in Machine Translation with Target Gender Annotationscited by 42
  5. 2020Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make Itcited by 40
  6. 2018Accelerating Neural Transformer via an Average Attention Networkcited by 22
  7. 2020Gender Bias in Multilingual Neural Machine Translation: The Architecture Matterscited by 11
  8. 2018Pieces of Eight: 8-bit Neural Machine Translationcited by 7
  9. 2017Deep Architectures for Neural Machine Translationcited by 5
  10. 2019Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Predictioncited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 11; 2023: 4; 2024: 9; 2025: 0; 2026: 2.

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  1. 2022"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Datasetcited by 160
  2. 2021A Survey on Gender Bias in Natural Language Processingcited by 89
  3. 2022Efficient Methods for Natural Language Processing: A Surveycited by 78
  4. 2022MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translationcited by 38
  5. 2022Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifoldcited by 29
  6. 2022Toxicity in Multilingual Machine Translation at Scalecited by 26
  7. 2021Hi, my name is Martha: Using names to measure and mitigate bias in generative dialogue modelscited by 23
  8. 2022Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translationcited by 23
  9. 2023Multilingual Holistic Bias: Extending Descriptors and Patterns to Unveil Demographic Biases in Languages at Scalecited by 23
  10. 2022Men Also Do Laundry: Multi-Attribute Bias Amplificationcited by 21
  11. 2023What about em? How Commercial Machine Translation Fails to Handle (Neo-)Pronounscited by 19
  12. 2023GATE: A Challenge Set for Gender-Ambiguous Translation Examplescited by 18
16 more
  1. 2024What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Studycited by 15
  2. 2022How sensitive are translation systems to extra contexts? Mitigating gender bias in Neural Machine Translation models through relevant contextscited by 10
  3. 2022What Do Compressed Multilingual Machine Translation Models Forget?cited by 9
  4. 2024MiTTenS: A Dataset for Evaluating Gender Mistranslationcited by 5
  5. 2024A Reality check of the benefits of LLM in businesscited by 5
  6. 2024GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languagescited by 4
  7. 2022The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translationcited by 3
  8. 2023The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languagescited by 3
  9. 2024FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbationscited by 3
  10. 2024Generating Gender Alternatives in Machine Translationcited by 3
  11. 2024The Trade-off between Performance, Efficiency, and Fairness in Adapter Modules for Text Classificationcited by 2
  12. 2024You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Modelscited by 2
  13. 2026KD4MT: A Survey of Knowledge Distillation for Machine Translationcited by 2
  14. 2022Screening Gender Transfer in Neural Machine Translationcited by 1
  15. 2024Towards Massive Multilingual Holistic Biascited by 0
  16. 2026Explaining GAND: A Resource on Gender-Ambiguous Natural Data & Contrastive Attributioncited by 0