ReasoNet: Learning to Stop Reading in Machine Comprehension讀書筆記
multi-hop reasoning閱讀理解，通過強化學習決定hop步數。 訓練技巧： 一般的baseline方法採用的是全局baseline，但是不同輸入的hop步數不同，採用全局baseline沒有區分。本文采用Constrastive Reward，對每個輸入單獨計算baseline，提高訓練速度。
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相關文章
- 1. 【論文筆記03】ReasoNet: Learning to Stop Reading in Machine Comprehension
- 2. machine-learning-yearning——讀書筆記
- 3. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 4. 論文筆記--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
- 5. 【論文筆記】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
- 6. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 論文閱讀筆記
- 7. 論文閱讀|Cross-Lingual Machine Reading Comprehension
- 8. 【論文翻譯+筆記】Neural Machine Reading Comprehension: Methods and Trends
- 9. Machine Learning Yearning讀書筆記（轉載）
- 10. Alibaba AI Model Tops Humans in Reading Comprehension