Papers with discourse-aware neural summarization model - DiscoBert

1 papers
Discourse-Aware Neural Extractive Text Summarization (2020.acl-main)

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Challenge: Recent studies have shown that sentence-based extractive models result in redundant or uninformative phrases in the extracted summaries.
Approach: They propose a discourse-aware neural summarization model that extracts sub-sentential discourse units as candidates for extractive selection on a finer granularity.
Outcome: Experiments show that the proposed model outperforms state-of-the-art models on popular summarization benchmarks.

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