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Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models
15 references·3 citing·44 second hop
Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models (2022)Upstream Mitigation Is Not All You Need: …Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers (2021)Towards a Comprehensive Under…Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle (2021)Toward Gender-Inclusive Coref…On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning (2021)On Transferability of Bias Mi…On the Opportunities and Risks of Foundation Models (2021)On the Opportunities and Risk…Large image datasets: A pyrrhic win for computer vision? (2021)Large image datasets: A pyrrh…Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases (2021)Image Representations Learned…Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development (2021)Do Datasets Have Politics? Di…Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias (2020)Unmasking Contextual Stereoty…Towards Debiasing Sentence Representations (2020)Towards Debiasing Sentence Re…Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Language (Technology) is Powe…On Measuring Social Biases in Sentence Encoders (2019)On Measuring Social Biases in…Measuring Bias in Contextualized Word Representations (2019)Measuring Bias in Contextuali…HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case (2019)HISTORIAE, History of Socio-C…Semantics derived automatically from language corpora contain human-like biases (2017)Semantics derived automatical…Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English (2017)Racial Disparity in Natural L…Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines (2024)Should Fairness be a Metric o…Overwriting Pretrained Bias with Finetuning Data (2023)Overwriting Pretrained Bias w…A Robust Bias Mitigation Procedure Based on the Stereotype Content Model (2022)A Robust Bias Mitigation Proc…Measuring individual differences in implicit cognition: The implicit association test. (1998)Fairness through awareness (2012)Big Data's Disparate Impact (2014)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Survey on Bias and Fairness in Machine Learning (2021)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Man is to Computer Programmer as Woman is to Homemaker? 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References

  • 2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case16,511 cited
  • 2017Semantics derived automatically from language corpora contain human-like biases2,845 cited
  • 2021On the Opportunities and Risks of Foundation Models2,670 cited
  • 2020Language (Technology) is Power: A Critical Survey of “Bias” in NLP1,044 cited
  • 2019On Measuring Social Biases in Sentence Encoders461 cited
  • 2019Measuring Bias in Contextualized Word Representations348 cited
  • 2021Large image datasets: A pyrrhic win for computer vision?258 cited
  • 2021Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development215 cited
  • 2021Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases159 cited
  • 2020Towards Debiasing Sentence Representations154 cited
  • 2017Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English100 cited
  • 2020Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias65 cited
  • 2021Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias Throughout the Machine Learning Lifecycle47 cited
  • 2021Towards a Comprehensive Understanding and Accurate Evaluation of Societal Biases in Pre-Trained Transformers

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44 cited
  • 2021On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning42 cited
  • Cited by

    • 2024Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines33 cited
    • 2023Overwriting Pretrained Bias with Finetuning Data24 cited
    • 2022A Robust Bias Mitigation Procedure Based on the Stereotype Content Model14 cited