Gender Bias Detection
7 papers with code • 0 benchmarks • 5 datasets
Benchmarks
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Latest papers with no code
FairShap: A Data Re-weighting Approach for Algorithmic Fairness based on Shapley Values
Algorithmic fairness is of utmost societal importance, yet the current trend in large-scale machine learning models requires training with massive datasets that are frequently biased.
Robots Enact Malignant Stereotypes
Stereotypes, bias, and discrimination have been extensively documented in Machine Learning (ML) methods such as Computer Vision (CV) [18, 80], Natural Language Processing (NLP) [6], or both, in the case of large image and caption models such as OpenAI CLIP [14].
Sparse Interventions in Language Models with Differentiable Masking
Typically, interpretation methods i) do not guarantee that the model actually uses the encoded information, and ii) do not discover small subsets of neurons responsible for a considered phenomenon.
Detecting Gender Bias in Transformer-based Models: A Case Study on BERT
In this paper, we propose a novel gender bias detection method by utilizing attention map for transformer-based models.
Second Order WinoBias (SoWinoBias) Test Set for Latent Gender Bias Detection in Coreference Resolution
We observe an instance of gender-induced bias in a downstream application, despite the absence of explicit gender words in the test cases.