HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization (P19-1)
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| Challenge: | Neural extractive summarization models employ hierarchical encoders with inaccurate sentence-level labels. |
| Approach: | They propose a method to pre-train a hierarchical encoder with unlabeled data. |
| Outcome: | The proposed model outperforms its initialized counterpart by 1.25 ROUGE on CNN and 2.0 ROUGEE on a version of New York Times dataset. |
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