《A Through Examination of the CNN_Daily Mail Reading Comprehension Task》——Stanford Attentive Reader
序 論文其他細節不再注意，只關注它的網絡結構。 可能是年代比較久遠，github上只有一個這篇論文的代碼…還是python2.7的 模型結構 模型分三部分： 第一部分，編碼：問題的詞編碼一樣，先通過一個embedding表，把詞編程embedding，然後過雙向GRU，前向和後向連在一起表示這個token出的表示，同樣對問題也編碼，只說了問題編碼後的維度：h,估計和其他論文一樣，都是前向後向的最後
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相關文章
- 1. A Thorough Examination of CNN/Daily Mail Reading Comprehension
- 2. 論文筆記《A Thorough Examination of CNN/Daliy Mail Reading Comprehension Task》
- 3. A Co-Matching Model for Multi-choice Reading Comprehension（譯）
- 4. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 5. 《 Text Understanding with the Attention Sum Reader Network 》——Attention Sum Reader
- 6. 【論文筆記03】ReasoNet: Learning to Stop Reading in Machine Comprehension
- 7. Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond
- 8. Alibaba AI Model Tops Humans in Reading Comprehension
- 9. Reading Note: Gated Self-Matching Networks for Reading Comprehension and Question Answering
- 10. 【論文翻譯+筆記】Neural Machine Reading Comprehension: Methods and Trends