论文阅读笔记《Ranking Sentences for Extractive Summarization with Reinforcement Learning》
文章目录 0 摘要 1 介绍 2 通过句子排序进行自动摘要 2.1 句子编码器(sentence encoder) 2.2 文档编码器(document encoder) 2.3 句子抽取器(sentence extractor) 3 交叉熵损失的陷阱 4 使用强化学习进行句子排序 4.1 策略学习(Policy Learning) 4.2 使用高概率样本进行训练 5 实验 5.1 摘要数据集 5
相关文章
- 1. Self-Supervised Learning for Contextualized Extractive Summarization
- 2. Machine Learning & Deep Learning 论文阅读笔记
- 3. FeUdal Networks for Hierarchical Reinforcement Learning 阅读笔记
- 4. 【论文笔记】Heterogeneous Graph Neural Networks for Extractive Document Summarization
- 5. Deep Reinforcement Learning for Dialogue Generation阅读笔记
- 6. 读论文2018 ACL A unified model for extractive and abstractive summarization using inconsistency loss
- 7. 论文笔记 Reinforcement Learning with Derivative-Free Exploration
- 8. 论文笔记——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
- 9. 论文笔记《Neural Architecture Search With Reinforcement Learning》
- 10. 【论文笔记】NEURAL COMBINATORIAL OPTIMIZATION WITH REINFORCEMENT LEARNING
- 更多相关文章...
- • RSS 阅读器 - RSS 教程
- • PHP 实例 - AJAX RSS 阅读器 - PHP教程
- • Tomcat学习笔记（史上最全tomcat学习笔记）
- • JDK13 GA发布：5大特性解读
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. Self-Supervised Learning for Contextualized Extractive Summarization
- 2. Machine Learning & Deep Learning 论文阅读笔记
- 3. FeUdal Networks for Hierarchical Reinforcement Learning 阅读笔记
- 4. 【论文笔记】Heterogeneous Graph Neural Networks for Extractive Document Summarization
- 5. Deep Reinforcement Learning for Dialogue Generation阅读笔记
- 6. 读论文2018 ACL A unified model for extractive and abstractive summarization using inconsistency loss
- 7. 论文笔记 Reinforcement Learning with Derivative-Free Exploration
- 8. 论文笔记——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
- 9. 论文笔记《Neural Architecture Search With Reinforcement Learning》
- 10. 【论文笔记】NEURAL COMBINATORIAL OPTIMIZATION WITH REINFORCEMENT LEARNING