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        <title>Transfer Learning from Pre-trained BERT for Pronoun Resolution</title>
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        <namePart type="given">Xingce</namePart>
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        <namePart type="given">Qianqian</namePart>
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            <title>Proceedings of the First Workshop on Gender Bias in Natural Language Processing</title>
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            <namePart type="given">Marta</namePart>
            <namePart type="given">R</namePart>
            <namePart type="family">Costa-jussà</namePart>
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        <name type="personal">
            <namePart type="given">Christian</namePart>
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            <namePart type="given">Will</namePart>
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    <abstract>The paper describes the submission of the team “We used bert!” to the shared task Gendered Pronoun Resolution (Pair pronouns to their correct entities). Our final submission model based on the fine-tuned BERT (Bidirectional Encoder Representations from Transformers) ranks 14th among 838 teams with a multi-class logarithmic loss of 0.208. In this work, contribution of transfer learning technique to pronoun resolution systems is investigated and the gender bias contained in classification models is evaluated.</abstract>
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    <identifier type="doi">10.18653/v1/W19-3812</identifier>
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%0 Conference Proceedings
%T Transfer Learning from Pre-trained BERT for Pronoun Resolution
%A Bao, Xingce
%A Qiao, Qianqian
%Y Costa-jussà, Marta R.
%Y Hardmeier, Christian
%Y Radford, Will
%Y Webster, Kellie
%S Proceedings of the First Workshop on Gender Bias in Natural Language Processing
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F bao-qiao-2019-transfer
%X The paper describes the submission of the team “We used bert!” to the shared task Gendered Pronoun Resolution (Pair pronouns to their correct entities). Our final submission model based on the fine-tuned BERT (Bidirectional Encoder Representations from Transformers) ranks 14th among 838 teams with a multi-class logarithmic loss of 0.208. In this work, contribution of transfer learning technique to pronoun resolution systems is investigated and the gender bias contained in classification models is evaluated.
%R 10.18653/v1/W19-3812
%U https://aclanthology.org/W19-3812
%U https://doi.org/10.18653/v1/W19-3812
%P 82-88

Markdown (Informal)

[Transfer Learning from Pre-trained BERT for Pronoun Resolution](https://aclanthology.org/W19-3812) (Bao & Qiao, GeBNLP 2019)

• Transfer Learning from Pre-trained BERT for Pronoun Resolution (Bao & Qiao, GeBNLP 2019)

ACL

• Xingce Bao and Qianqian Qiao. 2019. Transfer Learning from Pre-trained BERT for Pronoun Resolution. In Proceedings of the First Workshop on Gender Bias in Natural Language Processing, pages 82–88, Florence, Italy. Association for Computational Linguistics.