Dynamic Entity Representation with Max-pooling Improves Machine
本文是機器閱讀理解系列的第六篇文章，paper的題目是Dynamic Entity Representation with Max-pooling Improves Machine Reading，作者是來自日本東北大學的老師Sosuke Kobayashi，文章發表在NAACL HLT 2016。本文的代碼開源在Github。 本文模型之前的模型都是用一個靜態的向量來表示一個entity，與上下
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相關文章
- 1. 【論文筆記08】Dynamic Entity Representation with Max-pooling Improves Machine Reading
- 2. ERNIE: Enhanced Language Representation with Informative Entities
- 3. 【論文筆記】Representation Learning of Knowledge Graphs with Entity Descriptions
- 4. 論文筆記：Representation Learning of Knowledge Graphs with Entity Descriptions
- 5. Improving Named Entity Recognition for Chinese Social Media with Word Segmentation Representation Le
- 6. Machine Learning (3) Classification and Representation
- 7. Dynamic imports with webpack
- 8. Entity Framework with NOLOCK
- 9. Entity Framework With Oracle
- 10. 論文閱讀：Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation