【论文翻译+笔记】Neural Machine Reading Comprehension: Methods and Trends

时间 2021-07-12

标签 nlp MRC 论文综述繁體版

原文原文链接

1 Introduction 过去的MRC技术的特点：hand-crafted rules or features 缺点 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. 【论文笔记】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
2. Attention-over-Attention Neural Networks for Reading Comprehension论文笔记
3. 论文笔记--Multi-Style Generative Reading Comprehension (Masque)
4. 【论文笔记03】ReasoNet: Learning to Stop Reading in Machine Comprehension
5. 论文笔记--Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification (V-Net)
6. 论文笔记--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
7. 论文阅读|Cross-Lingual Machine Reading Comprehension
8. 论文《Adversarial Reading Networks For Machine Comprehension》
9. 机器阅读理解综述：2019—Neural Machine Reading Comprehension_Methods and Trends
10. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 论文阅读笔记

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