ACL 19 論文閱讀---Cognitive Graph for Multi-Hop Reading Comprehension at Scale （待完善）
1. 論文研讀筆記 1.1 研究動機 本文是唐傑老師組在ACL2019上的一篇長文。本文針對機器閱讀現在的三個挑戰：推理能力，可解釋性和規模性，論文基於Dual process theory設計了Cognitive Graph QA架構，來實現多跳的閱讀理解。下圖可以簡單展示本文的多跳閱讀的概念： 1.2 研究方法 本文的核心架構如下，系統1在抽取與問題相關的實體並編碼語義向量，系統2利用圖神經網
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相關文章
- 1. ACL 19 論文閱讀---Cognitive Graph for Multi-Hop Reading Comprehension at Scale （待完善）
- 2. #paper reading#Cognitive Graph for Multi-Hop Reading Comprehension at Scale
- 3. Cognitive Graph for Multi-Hop Reading Comprehension at Scale(ACL2019) 閱讀筆記及代碼解析
- 4. 論文閱讀|Cross-Lingual Machine Reading Comprehension
- 5. 【一起讀ACL論文】Attention-over-Attention Neural Networks for Reading Comprehension
- 6. 論文閱讀——Gated-Attention Readers for Machine Reading Comprehension
- 7. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記
- 8. 論文《Adversarial Reading Networks For Machine Comprehension》
- 9. ACL 2020 Contextualised Graph Attention for Improved Relation Extraction 論文閱讀
- 10. Joint Training of Candidate Extraction and Answer Selection for Reading Comprehension 論文閱讀筆記