【一起讀ACL論文】Attention-over-Attention Neural Networks for Reading Comprehension
一種針對完形填空式閱讀理解的模型。綜合來看，大概是雙向考慮了文檔->提問和提問->文檔的關係。思想和實現都是非常簡單的，從實驗結果來看效果不錯。而且也容易擴展到其他模型上。 整個模型如上圖所示。大概分爲三個部分： 和傳統模型類似，先把Document和Query都embedding出來（用的是GRU）。 根據向量表示計算出一個矩陣表示，記爲Pair-wise Matching Score. 表示查
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相關文章
- 1. Attention-over-Attention Neural Networks for Reading Comprehension 訊飛
- 2. 論文《Adversarial Reading Networks For Machine Comprehension》
- 3. 論文分享-->Attention-over-Attention Neural Networks for Reading Comprehension
- 4. Attention-over-Attention Neural Networks for Reading Comprehension論文筆記
- 5. 論文筆記《Consensus Attention-based Neural Networks for Chinese Reading Comprehension》
- 6. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記
- 7. 【博文筆記】AoA Reader_Attention-over-Attention Neural Networks for Reading Comprehension
- 8. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文筆記
- 9. ACL 19 論文閱讀---Cognitive Graph for Multi-Hop Reading Comprehension at Scale （待完善）
- 10. Consensus Attention-based Neural Networks for Chinese Reading