Papers by M. Kilavuz

1 papers
Language-Agnostic Bias Detection in Language Models with Bias Probing (2023.findings-emnlp)

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Challenge: Pretrained language models (PLMs) contain strong social biases, which are difficult to quantify because current methods focusing on fill-the-mask objectives are sensitive to slight changes in input.
Approach: They propose a bias probing technique called LABDet to evaluate social bias in pretrained language models with a language-agnostic method.
Outcome: The proposed method “surfaces” nationality bias by training a classifier on top of a frozen PLM on non-nationality sentiment detection.

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