Data-efficient domain adaptation for pretrained language models

Data-efficient domain adaptation for pretrained language models

Recent advances in Natural Language Processing (NLP) are built on a range of large-scale pretrained language models (PLMs), which are based on deep transformer neural networks. These PLMs simultaneously learn contextualized word representations and language modeling by training the entire model on m...

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Dades bibliogràfiques
Autor principal:	Guo, Xu
Altres autors:	Yu Han
Format:	Thesis-Doctor of Philosophy
Idioma:	English
Publicat:	Nanyang Technological University 2023
Matèries:	Engineering::Computer science and engineering
Accés en línia:	https://hdl.handle.net/10356/167965

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