Glyce: Glyph-vectors for Chinese Character Representations
本篇论文选自2019年NeurIPS，论文链接Glyce: Glyph-vectors for Chinese Character Representations 摘要 对于像中文这种象形文字，其字符本身形式就含有一定信息，但是由于象形文字缺乏丰富的象形证据以及标准计算机视觉模型对于字符数据的弱泛化能力，这种信息在NLP任务中没得到充分利用。 在本paper中提出Glyce，提出三点创新：(1)利
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相关文章
- 1. 【nlp论文笔记】 Glyce: Glyph-vectors for Chinese Character Representations
- 2. GitHub & puppeteer & Chinese character & bug
- 3. OHW系列之一《Stroke Sequence-Dependent DCNN for Online Handwritten Chinese Character Recognition 》
- 4. SLAM for Dummies （Chinese）(2)
- 5. 论文笔记：Enhancing Pre-trained Chinese Character Representation with Word-aligned Attention
- 6. 【论文学习】Combination of ResNet and Center Loss Based Metric Learning for Handwritten Chinese Character
- 7. 《Character-Based LSTM-CRF with Radical-Level Features for Chinese Named Entity Recognition》论文解读
- 8. sphinx-for-chinese linux安装
- 9. unmappable character for encoding ASCII
- 10. [转]awesome-tensorflow-chinese