Papers by Jeffrey Bowers

    1 papers
    Priorless Recurrent Networks Learn Curiously (2020.coling-main)

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    Challenge: a recent study shows domain-general recurrent neural networks reproduce human language behaviours . a lack of a unified concept of number agreement between these processes is a limitation of the model .
    Approach: They propose to use domain-general recurrent neural networks without explicit linguistic inductive biases to reproduce human language behaviours.
    Outcome: The proposed model can learn number agreement within unnatural sentences, the authors show . they show that the model has an effective understanding of singular versus plural for individual sentences .

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