Papers by Rosie Sallis

1 papers
First the Worst: Finding Better Gender Translations During Beam Search (2022.findings-acl)

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Challenge: Neural language generation models optimized by likelihood tend towards 'safe' word choice.
Approach: They propose to use beam search to improve gender diversity in n-best lists and rerank n best lists using gender features obtained from the source sentence to address this problem.
Outcome: The proposed approach improves gender diversity in n-best lists and reranks n best lists using gender features obtained from the source sentence.

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