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Chinese Word Segmentation On Cityu
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평가 결과
이 벤치마크에서 각 모델의 성능 결과
| Paper Title | ||
|---|---|---|
| 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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