Chinese Word Segmentation On Cityu
Metrics
F1
Results
Performance results of various models on this benchmark
Model Name | F1 | Paper Title | Repository |
|---|---|---|---|
| WMSeg + ZEN | 97.93 | Improving Chinese Word Segmentation with Wordhood Memory Networks | |
| Glyce + BERT | 97.9 | Glyce: Glyph-vectors for Chinese Character Representations |
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