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Zero-Shot Cross-lingual Transfer for XNLU

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

Task-oriented personal assistants enable people to interact with a host of devices and services using natural language. One of the challenges of making neural dialogue systems available to more users is the lack of training data for all but a few languages. Zero-shot methods try to solve this issue by acquiring task knowledge in a high-resource language such as English with the aim of transferring it to the low-resource language(s). I will present two ACL papers from ’21 and ’22 that propose a few novel methods for this application/purpose.

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

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