r-net:machine reading comprehension with self-matching networks
文章目錄 1.模型概述 2.passage和question編碼層 3.Gated Attention-based RNN 4.Self-Matching Attention 5.output layer 6.源碼和參數 參考鏈接 我覺得這篇文章的文筆真的有點不敢恭維，首先向量矩陣的維度不說清楚還能腦補，但是這邊前後不同層之間用一樣的變量名是什麼意思啊(這麼說出來會不會被MSRA鄙視，以後的簡歷都
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相關文章
- 1. r-net:machine reading comprehension with self-matching networks
- 2. Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
- 3. Attention-over-Attention Neural Networks for Reading Comprehension 訊飛
- 4. 論文《Adversarial Reading Networks For Machine Comprehension》
- 5. Reading Note: Gated Self-Matching Networks for Reading Comprehension and Question Answering
- 6. Cosmos QA：Machine reading comprehension with contextual commonsense reasoning
- 7. 【論文筆記】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
- 8. 論文分享-->Attention-over-Attention Neural Networks for Reading Comprehension
- 9. Simple and Effective Multi-Paragraph Reading Comprehension
- 10. #Paper Reading# Abstractive Sentence Summarization with Attentive Recurrent Neural Networks