.png){kind=icon}
返回
.png){kind=icon}
.png){kind=icon}
摘要
En 中文
NATURAL LANGUAGE PROCESSING (NLP) has undergone revolutionary changes in recent years. Thanks to the development and use of pre-trained language models, remarkable achievements have been made in many applications. Pre-trained language models offer two major advantages. One advantage is that they can significantly boost the accuracy of many NLP tasks. For example, one can exploit the BERT model to achieve performances higher than humans in language understanding.8 One can also leverage the GPT-3 model to generate texts that resemble human writings in language generation.3 A second advantage of pre-trained language models is that they are universal language processing tools. To conduct a machine learning-based task in traditional NLP, one had to label a large amount of data to train a model.
期刊
IF:
12.2
论文数:
1.2W
被引数:
3.7W
机构
暂无机构信息
引用论文
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏Phase Equilibria of Semiclathrate Hydrates of CO2, N2, CH4, or H2+ Tetra-n-butylammonium Bromide Aqueous SolutionPhase Equilibria of Semiclathrate Hydrates of CO2, N2, CH4,或H2 四-n-丁基溴化铵水溶液.png)
PREAI
分享收藏
查看更多内容