mlsanityData to 7 Oct 2026

Attenuating Bias in Word Vectors

arXiv 1901.07656 ↗First posted 23 Jan 2019cs.CLcited by 64

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Abstract (arXiv)

Word vector representations are well developed tools for various NLP and Machine Learning tasks and are known to retain significant semantic and syntactic structure of languages. But they are prone to carrying and amplifying bias which can perpetrate discrimination in various applications. In this work, we explore new simple ways to detect the most stereotypically gendered words in an embedding and remove the bias from them. We verify how names are masked carriers of gender bias and then use that as a tool to attenuate bias in embeddings. Further, we extend this property of names to show how names can be used to detect other types of bias in the embeddings such as bias based on race, ethnicity, and age.

Key facts. Cited by 64 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jan 2019.

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Citing papers per year: 2021: 18; 2022: 18; 2023: 12; 2024: 11; 2025: 3; 2026: 2.

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  1. 2021RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Modelscited by 149
  2. 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
  3. 2021Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologiescited by 128
  4. 2021Debiasing Pre-trained Contextualised Embeddingscited by 107
  5. 2021Sustainable Modular Debiasing of Language Modelscited by 98
  6. 2022Linear Adversarial Concept Erasurecited by 98
  7. 2023A Survey on Fairness in Large Language Modelscited by 91
  8. 2021A Survey on Gender Bias in Natural Language Processingcited by 89
  9. 2021Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metricscited by 83
  10. 2021On Measures of Biases and Harms in NLPcited by 81
  11. 2022Theories of "Gender" in NLP Bias Researchcited by 62
  12. 2022Gender Bias in Masked Language Models for Multiple Languagescited by 60
38 more
  1. 2022Kernelized Concept Erasurecited by 47
  2. 2022Quantifying Societal Bias Amplification in Image Captioningcited by 37
  3. 2024Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicitycited by 33
  4. 2022MABEL: Attenuating Gender Bias using Textual Entailment Datacited by 31
  5. 2021Socially Aware Bias Measurements for Hindi Language Representationscited by 29
  6. 2021Fair Representation Learning for Heterogeneous Information Networkscited by 28
  7. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 27
  8. 2023Zero-Shot Robustification of Zero-Shot Modelscited by 24
  9. 2025Beyond Linear Steering: Unified Multi-Attribute Control for Language Modelscited by 23
  10. 2022Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Surveycited by 22
  11. 2022Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisementscited by 21
  12. 2021Evaluating Gender Bias in Hindi-English Machine Translationcited by 19
  13. 2024Fairness and Bias in Multimodal AI: A Surveycited by 19
  14. 2022Fair and Argumentative Language Modeling for Computational Argumentationcited by 18
  15. 2022USCORE: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translationcited by 15
  16. 2023Kiki or Bouba? Sound Symbolism in Vision-and-Language Modelscited by 14
  17. 2021Diachronic Analysis of German Parliamentary Proceedings: Ideological Shifts through the Lens of Political Biasescited by 13
  18. 2023CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Biascited by 13
  19. 2024AGR: Age Group fairness Reward for Bias Mitigation in LLMscited by 12
  20. 2021Word Embeddings via Causal Inference: Gender Bias Reducing and Semantic Information Preservingcited by 11
  21. 2023Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLPcited by 11
  22. 2021WordBias: An Interactive Visual Tool for Discovering Intersectional Biases Encoded in Word Embeddingscited by 8
  23. 2021Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languagescited by 8
  24. 2023Representation Of Lexical Stylistic Features In Language Models' Embedding Spacecited by 8
  25. 2022Mitigating Gender Stereotypes in Hindi and Marathicited by 6
  26. 2021DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spacescited by 5
  27. 2021Obstructing Classification via Projectioncited by 5
  28. 2022No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Mediacited by 5
  29. 2022Bridging Fairness and Environmental Sustainability in Natural Language Processingcited by 5
  30. 2023Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimationcited by 5
  31. 2021User Acceptance of Gender Stereotypes in Automated Career Recommendationscited by 4
  32. 2022Undesirable Biases in NLP: Addressing Challenges of Measurementcited by 4
  33. 2024Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Wayscited by 4
  34. 2024Adjusting Interpretable Dimensions in Embedding Space with Human Judgmentscited by 4
  35. 2025On the Mutual Influence of Gender and Occupation in LLM Representationscited by 4
  36. 2021VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representationscited by 3
  37. 2022Towards Debiasing Translation Artifactscited by 3
  38. 2024Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approachcited by 3

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