Papers by Francesco Saina
DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation (2022.acl-long)
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| Challenge: | Lexical ambiguity poses one of the greatest challenges in the field of Machine Translation. |
| Approach: | They propose a new benchmark to study semantic biases in Machine Translation of nominal and verbal words in five different languages. |
| Outcome: | The proposed benchmark tests state-of-the-art machine translation systems against the new test bed and provides a statistical and linguistic analysis of the results. |