Pre-trained Models for Natural Language Processing: A Survey
Published in SCIENCE CHINA Technological Sciences (SCTS), 2020
Recommended citation: Xipeng Qiu, TianXiang Sun, Yige Xu, Yunfan Shao, Ning Dai, Xuanjing Huang, Pre-trained Models for Natural Language Processing: A Survey, SCIENCE CHINA Technological Sciences (SCTS) , 2020, Vol. 63(10), pp. 1872–1897 http://xuanjing-huang.github.io/files/PTM.pdf
Recently, the emergence of pre-trained models (PTMs) has brought natural language processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs for NLP. We first briefly introduce language representation learning and its research progress. Then we systematically categorize existing PTMs based on a taxonomy from four different perspectives. Next, we describe how to adapt the knowledge of PTMs to downstream tasks. Finally, we outline some potential directions of PTMs for future research. This survey is purposed to be a hands-on guide for understanding, using, and developing PTMs for various NLP tasks.