An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework Based on Semantic Blocks (2022.coling-1)
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| Challenge: | Existing unsupervised summarization methods fail to consider efficiency and effectiveness when the input document is extremely long. |
| Approach: | They propose an efficient Coarse-to-Fine Facet-Aware Ranking framework for unsupervised long document summarization based on the semantic block. |
| Outcome: | The proposed framework can achieve new state-of-the-art unsupervised summarization results on Gov-Report, billSum, arXiv, and PubMed. |
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