Get to the point: summarization with pointer-generator networks阅读
简介： 基于注意力机制的Seq2Seq模型，使用每一步解码的隐层状态与编码器的隐层状态计算权重，最终得到context向量，利用context向量和解码器隐层状态计算输出概率。这篇文章主要试图解决问题1、无法准确复述原文细节，无法处理不在词表中的词(oov问题) 2、生成的在摘要中存在重复的片段 Pointer-generator network模型结构图： 主要贡献点：
相关文章
- 1. [ACL2017] Get to The Point: Summarization with Pointer-Generator Networks
- 2. 【论文阅读】Get to the point :summarization with pointer-generator networks
- 3. PGN: 指针生成网络（Get To The Point: Summarization with Pointer-Generator Networks）
- 4. 指针生成网络 Pointer-Generator《Get To The Point: Summarization with Pointer-Generator Networks》论文阅读笔记
- 5. 论文阅读： Going Deeper with Point Networks
- 6. Get to the pointer：Abstractvie summarization with pointer-generator networks（指向生成器网络）---2017ACL
- 7. 论文阅读 《Text Summarization with Pretrained Encoders》
- 8. 论文阅读笔记：From Image-level to Pixel-level Labeling with Convolutional Networks
- 9. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization
- 10. 论文--阅读翻译笔记-Reducing the Dimensionality of Data with Neural Networks
- 更多相关文章...
- • RSS 阅读器 - RSS 教程
- • PHP 实例 - AJAX RSS 阅读器 - PHP教程
- • JDK13 GA发布：5大特性解读
- • 为了进字节跳动，我精选了29道Java经典算法题，带详细讲解
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. [ACL2017] Get to The Point: Summarization with Pointer-Generator Networks
- 2. 【论文阅读】Get to the point :summarization with pointer-generator networks
- 3. PGN: 指针生成网络（Get To The Point: Summarization with Pointer-Generator Networks）
- 4. 指针生成网络 Pointer-Generator《Get To The Point: Summarization with Pointer-Generator Networks》论文阅读笔记
- 5. 论文阅读： Going Deeper with Point Networks
- 6. Get to the pointer：Abstractvie summarization with pointer-generator networks（指向生成器网络）---2017ACL
- 7. 论文阅读 《Text Summarization with Pretrained Encoders》
- 8. 论文阅读笔记：From Image-level to Pixel-level Labeling with Convolutional Networks
- 9. Ranking with Recursive Neural Networks and Its Application to Multi-document Summarization
- 10. 论文--阅读翻译笔记-Reducing the Dimensionality of Data with Neural Networks