A Deep Cascade Model for Multi-Document Reading Comprehension瀑布模型 閱讀理解筆記
《A Deep Cascade Model for Multi-Document Reading Comprehension》 這篇文章是發表在2019年AAAI上的，主要是從抽取模型的有效性和候選排序模型的實效性進行權衡，提出了一種端到端的瀑布模型。在TriviaQA和DuReader數據集上得到了SOTA效果。 分以下四部分介紹： Motivation Model Experiment Dis
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相關文章
- 1. A Co-Matching Model for Multi-choice Reading Comprehension（譯）
- 2. Gated Self-Matching Networks for Reading Comprehension and Question Answering論文閱讀筆記
- 3. A Compact Deep Learning Model for Robust Facial Expression Recognition 閱讀筆記
- 4. Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension閱讀筆記
- 5. 閱讀理解BI-DAF《BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION》筆記
- 6. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 論文閱讀筆記
- 7. Deep Convolutional Network Cascade for Facial Point Detection閱讀筆記
- 8. V-Net 《Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification》閱讀理解筆記
- 9. Cognitive Graph for Multi-Hop Reading Comprehension at Scale(ACL2019) 閱讀筆記及代碼解析
- 10. 強化學習《A DEEP REINFORCED MODEL FOR ABSTRACTIVE SUMMARIZATION》論文閱讀筆記