HIGHLIGHTS
- who: Unknown from the School of Computer Science and Technology, Dalian University of Technology, Dalian, China have published the Article: Exploiting Intersentence Information for Better Question-Driven Abstractive Summarization: Algorithm Development and Validation, in the Journal: (JOURNAL)
- what: The question-answering task demonstrates that the generated summaries of the model have better factual constancy. In this paper, a novel question-driven abstractive summarization based on transformer is proposed, namely Trans-Att, that incorporates a two-step attention mechanism and an overall integration mechanism to summarize the document with respect to the nonfactoid questions. The authors . . .
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