Analyzing Sentence Fusion in Abstractive Summarization
October 01, 2019 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
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Authors
Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu
arXiv ID
1910.00203
Category
cs.CL: Computation & Language
Citations
43
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
4 months ago
Abstract
While recent work in abstractive summarization has resulted in higher scores in automatic metrics, there is little understanding on how these systems combine information taken from multiple document sentences. In this paper, we analyze the outputs of five state-of-the-art abstractive summarizers, focusing on summary sentences that are formed by sentence fusion. We ask assessors to judge the grammaticality, faithfulness, and method of fusion for summary sentences. Our analysis reveals that system sentences are mostly grammatical, but often fail to remain faithful to the original article.
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