Glyce: Glyph-vectors for Chinese Character Representations
本篇論文選自2019年NeurIPS，論文鏈接Glyce: Glyph-vectors for Chinese Character Representations 摘要 對於像中文這種象形文字，其字符本身形式就含有一定信息，但是由於象形文字缺乏豐富的象形證據以及標準計算機視覺模型對於字符數據的弱泛化能力，這種信息在NLP任務中沒得到充分利用。 在本paper中提出Glyce，提出三點創新：(1)利
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相關文章
- 1. 【nlp論文筆記】 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. 論文筆記：Enhancing Pre-trained Chinese Character Representation with Word-aligned Attention
- 6. 【論文學習】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》論文解讀
- 8. sphinx-for-chinese linux安裝
- 9. unmappable character for encoding ASCII
- 10. [轉]awesome-tensorflow-chinese