HIBERT Document Level Pre-training of Hierarchical Bi-Transformers for Document Summarization
ACL 2019 HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization 背景 对于抽取式摘要生成来说，模型最终的任务是为文档中的句子分配对应的标签，从而来表示某个句子是否会出现在最后的摘要中。因此，抽取式任务本质上可以看做是： 句子排序任务：
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相关文章
- 1. 12.10 抽取式摘要论文阅读 HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for D
- 2. Hierarchical Attention Networks for Document Classification
- 3. HAN(Hierarchical Attention Networks for Document Classification)
- 4. attention model -- Hierarchical Attention Networks for Document Classification
- 5. Hierarchical Attention Network for Document Classification阅读笔记
- 6. Heterogeneous Graph Neural Networks for Extractive Document Summarization
- 7. ACL2020 Heterogeneous Graph Neural Networks for Extractive Document Summarization
- 8. Hierarchical Attention Networks for Document Classification学习笔记
- 9. paper:Hierarchical Attention Networks for Document Classification
- 10. Double Graph Based Reasoning for Document-level Relation Extraction（EMNLP2020）