Search Results for author: Vishal Chowdhary

Found 6 papers, 2 papers with code

GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages

no code implementations22 Feb 2024 Spencer Rarrick, Ranjita Naik, Sundar Poudel, Vishal Chowdhary

Neural Machine Translation (NMT) continues to improve in quality and adoption, yet the inadvertent perpetuation of gender bias remains a significant concern.

Machine Translation NMT +2

Reducing Gender Bias in Machine Translation through Counterfactual Data Generation

no code implementations27 Nov 2023 Ranjita Naik, Spencer Rarrick, Vishal Chowdhary

By using this data to fine-tune an existing NMT model, they show that gender bias can be significantly mitigated, albeit at the expense of translation quality due to catastrophic forgetting.

counterfactual Domain Adaptation +3

Evaluating Gender Bias in the Translation of Gender-Neutral Languages into English

no code implementations15 Nov 2023 Spencer Rarrick, Ranjita Naik, Sundar Poudel, Vishal Chowdhary

To address this gap, we introduce GATE X-E, an extension to the GATE (Rarrick et al., 2023) corpus, that consists of human translations from Turkish, Hungarian, Finnish, and Persian into English.

Machine Translation Sentence +1

GATE: A Challenge Set for Gender-Ambiguous Translation Examples

1 code implementation7 Mar 2023 Spencer Rarrick, Ranjita Naik, Varun Mathur, Sundar Poudel, Vishal Chowdhary

Although recent years have brought significant progress in improving translation of unambiguously gendered sentences, translation of ambiguously gendered input remains relatively unexplored.

Machine Translation Translation

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