Glyce: Glyph-vectors for Chinese Character Representations
Table 5: Results for sentence-pair classification tasks.
['LCQMC Model', 'LCQMC P', 'LCQMC R', 'LCQMC F', 'LCQMC A']
The current non-BERT SOTA model is based on the bilateral multi-perspective matching model (BiMPM) Glyph embeddings are incorporated into BiMPMs, forming the Glyce+BiMPM baseline. As can be seen, BiPMP+Glyce outperforms BiPMPs, achieving the best results among non-bert models. BERT outperforms all non-BERT models, and BERT+Glyce performs the best, setting new SOTA results on all of the four benchmarks.