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Speaker: Francois Meyer Title: Data-Efficient Language Modelling for Low-Resource Languages Abstract: Progress in language modelling has been driven by scaling data and model size, but this approach is not feasible for most African languages. In this talk, I will present our work on developing data-efficient language models - architectures and training algorithms that improve performance on limited training data. I will present examples of how linguistically informed modelling, which targets and leverages the linguistic properties of specific languages, can improve sample efficiency. Finally, I will discuss the emerging intersection between low-resource NLP and developmentally inspired NLP, exploring how insights from human language learning can help us build more efficient models. Biography: Francois Meyer is a Lecturer in the Computer Science Department at the University of Cape Town and co-investigator in the UCT NLP research group. His research is on data-efficient language modelling and linguistically informed sub-word tokenisation. He completed his PhD at the University of Cape Town and previously obtained a masters in AI at the University of Amsterdam.
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