Ayrton San Joaquin’s scientific contributions

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Publications (1)

Figure 1: Validation Accuracies for the Different Languages using four different input feature representations.
Figure 3: Integrated Gradients (IG) attribution for a single example. We identify salient features common within class examples and craft adversarial examples by replacing those features with the salient features of the other class.
Applying Multilingual Models to Question Answering (QA)
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December 2022

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Ayrton San Joaquin

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Filip Skubacz

We study the performance of monolingual and multilingual language models on the task of question-answering (QA) on three diverse languages: English, Finnish and Japanese. We develop models for the tasks of (1) determining if a question is answerable given the context and (2) identifying the answer texts within the context using IOB tagging. Furthermore, we attempt to evaluate the effectiveness of a pre-trained multilingual encoder (Multilingual BERT) on cross-language zero-shot learning for both the answerability and IOB sequence classifiers.

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