NeurIPS 2019poster259 citations
Glyce: Glyph-vectors for Chinese Character Representations
Yuxian Meng, Wei Wu, Fei Wang, Xiaoya Li, Ping Nie, Fan Yin, Muyu Li, Qinghong Han
Abstract
It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the use of the glyph information in those languages. However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.
BibTeX
@inproceedings{NEURIPS2019_452bf208,
author = {Meng, Yuxian and Wu, Wei and Wang, Fei and Li, Xiaoya and Nie, Ping and Yin, Fan and Li, Muyu and Han, Qinghong and Sun, Xiaofei and Li, Jiwei},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Glyce: Glyph-vectors for Chinese Character Representations},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/452bf208bf901322968557227b8f6efe-Paper.pdf},
volume = {32},
year = {2019}
}