Template Based Neural Summarization Models
ACL 2018 《Retrieve,Rerank and Rewrite: Soft Template Based Neural Summarization》 github[原文中给的已失效，网上也没有找到源码 ] 传统上基于Seq2Seq的摘要生成模型尽管可以得到较高的ROUGE，但是得到的摘要仍存在着很多问题： 模型生成的摘要过短，有3%的摘要包含的词少于3个 随着摘要长度的增加，生成性能急
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相关文章
- 1. Development of Neural Network Models in Text Summarization - 4
- 2. [论文阅读]《A Template-based Abstractive Meeting Summarization》
- 3. Extractive Summarization using Continuous Vector Space Models
- 4. Neural Summarization by Extracting Sentences and Words
- 5. Taming Recurrent Neural Networks for Better Summarization
- 6. SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documen
- 7. （转）awesome-text-summarization
- 8. #Paper Reading# Neural Extractive Summarization with Side Information
- 9. #Paper Reading# A Neural Attention Model for Abstractive Sentence Summarization
- 10. [Scikit-learn] 1.1 Generalized Linear Models - Neural network models