《A Through Examination of the CNN_Daily Mail Reading Comprehension Task》——Stanford Attentive Reader
序 论文其他细节不再注意，只关注它的网络结构。 可能是年代比较久远，github上只有一个这篇论文的代码…还是python2.7的 模型结构 模型分三部分： 第一部分，编码：问题的词编码一样，先通过一个embedding表，把词编程embedding，然后过双向GRU，前向和后向连在一起表示这个token出的表示，同样对问题也编码，只说了问题编码后的维度：h,估计和其他论文一样，都是前向后向的最后
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相关文章
- 1. A Thorough Examination of CNN/Daily Mail Reading Comprehension
- 2. 论文笔记《A Thorough Examination of CNN/Daliy Mail Reading Comprehension Task》
- 3. A Co-Matching Model for Multi-choice Reading Comprehension（译）
- 4. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 5. 《 Text Understanding with the Attention Sum Reader Network 》——Attention Sum Reader
- 6. 【论文笔记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
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- 10. 【论文翻译+笔记】Neural Machine Reading Comprehension: Methods and Trends