no code implementations • AACL (NLP-TEA) 2020 • Meiyuan Fang, Kai Fu, JiPing Wang, Yang Liu, Jin Huang, Yitao Duan
As a result, among the six tracks in the shared task, our system performs well in the correction tracks: measured in F1 score, we rank first, with the highest precision, in the TOP3 correction track and third in the TOP1 correction track, also with the highest precision.
no code implementations • 7 Jun 2022 • Youzhi Qu, Xinyao Jian, Wenxin Che, Penghui Du, Kai Fu, Quanying Liu
Transfer learning improves the performance of the target task by leveraging the data of a specific source task: the closer the relationship between the source and the target tasks, the greater the performance improvement by transfer learning.