Papers with Comprehensive document encoding
Improving Abstractive Document Summarization with Salient Information Modeling (P19-1)
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| Challenge: | Abstractive document summarization is a task of natural language generation which generates fluent summaries with salient information automatically. |
| Approach: | They propose to incorporate a Gaussian focal bias on attention scores into an encoder to enhance the perception of local context and to distinguish salient information precisely. |
| Outcome: | The proposed framework outperforms state-of-the-art models on the CNN/Daily Mail benchmark and is based on a focus-attention mechanism and two new extensions. |