Attentive Pooling Networks論文講解
這篇論文是做是一個做問答對匹配的模型，在多個回答裏選出正確的那個答案，整篇論文相對簡單。 之前的問答對匹配模型是將CNN或者BiLSTM提取後的特徵向量相互做餘弦相似度，這篇論文的創新是加上了Attention層和使用不同的pooling層，column-wise max pooling 和 row-wise max pooling 之前的模型是 本篇論文的模型是 Q 和 A 是問題和答案通過CN
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相關文章
- 1. Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks論文解讀
- 2. Attentive Sequence to Sequence Networks
- 3. 論文筆記：Gazetteer-Enhanced Attentive Neural Networks for Named Entity Recognition
- 4. 講解 Spatial Pyramid Pooling
- 5. A Structured Self-attentive Sentence Embedding 論文筆記
- 6. Deformable ConvNets--Part4：Deformable Convolutional Networks論文解讀
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- 10. 論文閱讀 # Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks