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Due to their similarity-based learning objectives, pretrained sentence encoders often internalize stereotypical assumptions that reflect the social biases that exist within their training corpora.
Language models are few-shot learners
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Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2004
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Deberta: Decoding-enhanced bert with disentangled attention
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Towards debiasing sentence representations
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Unmasking contextual stereotypes: Measuring and mitigating bert’s gender bias
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Making pre-trained language models better -shot learners
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