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 對於抽取式摘要生成來說，模型最終的任務是爲文檔中的句子分配對應的標籤，從而來表示某個句子是否會出現在最後的摘要中。因此，抽取式任務本質上可以看做是： 句子排序任務：
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相關文章
- 1. 12.10 抽取式摘要論文閱讀 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閱讀筆記
- 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學習筆記
- 9. paper:Hierarchical Attention Networks for Document Classification
- 10. Double Graph Based Reasoning for Document-level Relation Extraction（EMNLP2020）