35 citations · 43 across the 9 of their papers we have counts for
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cs.CL2023
Concept-Based Explanations to Test for False Causal Relationships Learned by Abusive Language Classifiers
Isar Nejadgholi, Svetlana Kiritchenko, Kathleen C. Fraser +1
Classifiers tend to learn a false causal relationship between an over-represented concept and a label, which can result in over-reliance on the concept and compromised classificati…
cs.CL2023★ 2 cited
This Prompt is Measuring <MASK>: Evaluating Bias Evaluation in Language Models
Seraphina Goldfarb-Tarrant, Eddie Ungless, Esma Balkir +1
Bias research in NLP seeks to analyse models for social biases, thus helping NLP practitioners uncover, measure, and mitigate social harms. We analyse the body of work that uses pr…