Template Based Neural Summarization Models
ACL 2018 《Retrieve,Rerank and Rewrite: Soft Template Based Neural Summarization》 github[原文中給的已失效，網上也沒有找到源碼 ] 傳統上基於Seq2Seq的摘要生成模型儘管可以得到較高的ROUGE，但是得到的摘要仍存在着很多問題： 模型生成的摘要過短，有3%的摘要包含的詞少於3個 隨着摘要長度的增加，生成性能急
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相關文章
- 1. Development of Neural Network Models in Text Summarization - 4
- 2. [論文閱讀]《A Template-based Abstractive Meeting Summarization》
- 3. Extractive Summarization using Continuous Vector Space Models
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- 5. Taming Recurrent Neural Networks for Better Summarization
- 6. SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documen
- 7. （轉）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