論文《Adversarial Reading Networks For Machine Comprehension》
綜述:文中描述當前閱讀理解任務中受限於監督學習設置，以及可用的數據集。這篇論文主要提出關於閱讀理解任務中的對抗學習以及self-play.它用一個名爲reader network來找到關於text和query的答案，還用一個名爲narrator network的網絡來混淆text的內容，來降低reader network網絡成功的可能性。然後取得了較好的效果。 文章的貢獻: 1,提出了一個新的基於
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相關文章
- 1. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 2. 論文閱讀|Cross-Lingual Machine Reading Comprehension
- 3. Attention-over-Attention Neural Networks for Reading Comprehension論文筆記
- 4. Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
- 5. 論文閱讀——Gated-Attention Readers for Machine Reading Comprehension
- 6. 論文筆記--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
- 7. 論文分享-->Attention-over-Attention Neural Networks for Reading Comprehension
- 8. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文筆記
- 9. 【一起讀ACL論文】Attention-over-Attention Neural Networks for Reading Comprehension
- 10. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記