ReasoNet: Learning to Stop Reading in Machine Comprehension读书笔记
multi-hop reasoning阅读理解，通过强化学习决定hop步数。 训练技巧： 一般的baseline方法采用的是全局baseline，但是不同输入的hop步数不同，采用全局baseline没有区分。本文采用Constrastive Reward，对每个输入单独计算baseline，提高训练速度。
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相关文章
- 1. 【论文笔记03】ReasoNet: Learning to Stop Reading in Machine Comprehension
- 2. machine-learning-yearning——读书笔记
- 3. A Robust Adversarial Training Approach to Machine Reading Comprehension
- 4. 论文笔记--From Answer Extraction to Answer Generation for Machine Reading Comprehension (S-Net)
- 5. 【论文笔记】Improving Machine Reading Comprehension with General Reading Strategies（2019，NAACL）
- 6. Read + Verify: Machine Reading Comprehension with Unanswerable Questions 论文阅读笔记
- 7. 论文阅读|Cross-Lingual Machine Reading Comprehension
- 8. 【论文翻译+笔记】Neural Machine Reading Comprehension: Methods and Trends
- 9. Machine Learning Yearning读书笔记（转载）
- 10. Alibaba AI Model Tops Humans in Reading Comprehension