Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks
empirical methods in natural language processing, pp. 7635-7653, 2020.
Word sense disambiguation is a well-known source of translation errors in NMT. We posit that some of the incorrect disambiguation choices are due to models’ over-reliance on dataset artifacts found in training data, specifically superficial word co-occurrences, rather than a deeper understanding of the source text. We introduce a method f...More
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