Papers by Alba Táboas García

1 papers
Assessing the Syntactic Capabilities of Transformer-based Multilingual Language Models (2021.findings-acl)

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Challenge: Multilingual Transformer-based language models have been shown to be excellent learners in crosslingual transfer tasks.
Approach: They evaluate the syntactic generalization capabilities of BERT and RoBERTa models on English and Spanish tests.
Outcome: The proposed models perform well on English and Spanish tests, and the proposed tests are compared against models on the same language and models on two different languages.

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