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Cross-lingual Learning, and Applications in Dialog and Translation

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If you have a question about this talk, please contact Marinela Parovic.

Over the last decade, the phenomenal success of NLP systems has been mostly driven by deep neural networks and supervised machine learning approaches to a large amount of labeled data. However, it’s infeasible to annotate data under all possible real-world scenarios. As a result, these systems may fail dramatically in practice when dealing with complex textual data written in different languages, or even associated with different data modalities. In this talk, I will present works that are important to extend the generalization ability of NLP systems across languages. First, I will present our work on XTREME which provides a platform for cross-lingual learning on 9 NLP tasks in 40 languages. ​​I will then demonstrate two cross-lingual applications of task-oriented dialog and machine translation. This talk will be concluded with an overview of my research and some future directions.

This talk is part of the Language Technology Lab Seminars series.

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