Reviews: Glyce: Glyph-vectors for Chinese Character Representations

This paper describes a method for leveraging sub-character information from Chinese characters, and reports small but reliable improvements on a large number of Chinese NLP tasks. The paper is strong in the results that it reports. The authors show that incorporation of their "Glyce" embeddings improves results from BERT (which is SOTA on nearly all of the tasks), as well the strongest non-BERT models, for a wide variety of tasks. So it appears that the authors' methods have successfully allowed them to leverage some useful signal from the sub-character information, which seems a reasonably significant contribution for Chinese NLP. The main weakness of the paper is in clarity of the methods.