【論文翻譯+筆記】Neural Machine Reading Comprehension: Methods and Trends

時間 2021-07-12

標籤 nlp MRC 論文綜述简体版

原文原文鏈接

1 Introduction 過去的MRC技術的特點：hand-crafted rules or features 缺點 Incapable of generalization performance may degrade due to large-scale datasets of myriad types of articles ignore long-range dependencies

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1. 【論文筆記】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
2. Attention-over-Attention Neural Networks for Reading Comprehension論文筆記
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6. 論文筆記--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
7. 論文閱讀|Cross-Lingual Machine Reading Comprehension
8. 論文《Adversarial Reading Networks For Machine Comprehension》
9. 機器閱讀理解綜述：2019—Neural Machine Reading Comprehension_Methods and Trends
10. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 論文閱讀筆記
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1. 【論文筆記】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
2. Attention-over-Attention Neural Networks for Reading Comprehension論文筆記
3. 論文筆記--Multi-Style Generative Reading Comprehension (Masque)
4. 【論文筆記03】ReasoNet: Learning to Stop Reading in Machine Comprehension
5. 論文筆記--Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification (V-Net)
6. 論文筆記--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
7. 論文閱讀|Cross-Lingual Machine Reading Comprehension
8. 論文《Adversarial Reading Networks For Machine Comprehension》
9. 機器閱讀理解綜述：2019—Neural Machine Reading Comprehension_Methods and Trends
10. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 論文閱讀筆記

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