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IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation ...
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Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer ...
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Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer ...
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Adapting Monolingual Models: Data can be Scarce when Language Similarity is High ...
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Generic resources are what you need: Style transfer tasks without task-specific parallel training data ...
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Adapting Monolingual Models: Data can be Scarce when Language Similarity is High ...
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As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languages ...
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Teaching NLP with Bracelets and Restaurant Menus: An Interactive Workshop for Italian Students ...
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Teaching NLP with Bracelets and Restaurant Menus:An Interactive Workshop for Italian Students
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What's so special about BERT's layers? A closer look at the NLP pipeline in monolingual and multilingual models ...
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Personal-ITY: A Novel YouTube-based Corpus for Personality Prediction in Italian ...
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Datasets and Models for Authorship Attribution on Italian Personal Writings ...
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Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias ...
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Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality ...
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Unmasking Contextual Stereotypes: Measuring and Mitigating BERT'S Gender Bias ...
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Abstract:
Is it possible to draw a line between workforce statistics and gender bias in contextualized word embeddings? Focusing on BERT (Devlin et al., 2018), we measure gender bias by studying associations between gender-denoting target words and names of professions (Kurita et al., 2019), offering two further perspectives: a comparison with U.S. labor statistics as well as a cross-lingual approach. We mitigate bias by fine-tuning BERT on the GAP corpus (Webster et al., 2018), after applying Counterfactual Data Substitution (CDS; Maudslay et al., 2019). While our method of measuring bias is appropriate for languages such as English, it is not suitable for languages with gender-marking, such as German. Our results highlight the importance of investigating bias and mitigation techniques cross-linguistically and connect large-scale language models to real-world data. ...
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Keyword:
Natural Language Processing
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URL: https://underline.io/lecture/6595-unmasking-contextual-stereotypes-measuring-and-mitigating-bert's-gender-bias https://dx.doi.org/10.48448/j5m3-4d93
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As Good as New. How to Successfully Recycle English GPT-2 to Make Models for Other Languages ...
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Fair Is Better than Sensational: Man Is to Doctor as Woman Is to Doctor
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In: Computational Linguistics, Vol 46, Iss 2, Pp 487-497 (2020) (2020)
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