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Overwriting Pretrained Bias with Finetuning Data
16 references·0 citing·37 second hop
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References

  • 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification3,509 cited
  • 2019Model Cards for Model Reporting2,653 cited
  • 2016Equality of Opportunity in Supervised Learning2,535 cited
  • 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints829 cited
  • 2021“Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI774 cited
  • 2020Data and its (dis)contents: A survey of dataset development and use in machine learning research519 cited
  • 2019Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations355 cited
  • 2021Large image datasets: A pyrrhic win for computer vision?258 cited
  • 2020Lessons from archives240 cited
  • 2018Gender Recognition or Gender Reductionism?222 cited
  • 2021Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development215 cited
  • 2017No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World173 cited
  • 2021Image Representations Learned With Unsupervised Pre-Training Contain Human-like Biases159 cited
  • 2021Multimodal datasets: misogyny, pornography, and malignant stereotypes157 cited

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2021
Fair Attribute Classification through Latent Space De-biasing
123 cited
  • 2020An Investigation of Why Overparameterization Exacerbates Spurious Correlations122 cited
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