Papers with semantic text matching problem

1 papers
Extractive Summarization as Text Matching (2020.acl-main)

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Challenge: Currently, most of the neural extractive summarization systems score and extract sentences individually and model the relationship between sentences.
Approach: They propose to instantiate a neural extractive summarization task as a semantic text matching problem and use it to match a source document and candidate summaries in a semantic space.
Outcome: The proposed framework is faster and more efficient than existing frameworks.

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