08/12/2020

Fine-tuning Neural Machine Translation on Gender-Balanced Datasets

Marta R. Costa-jussà, Adrià de Jorge

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Abstract: Misrepresentation of certain communities in datasets is causing big disruptions in artificial intelligence applications. In this paper, we propose using an automatically extracted gender-balanced dataset parallel corpus from Wikipedia. This balanced set is used to perform fine-tuning techniques from a bigger model trained on unbalanced datasets to mitigate gender biases in neural machine translation.

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