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End-to-End Segmentation-based News Summarization
[article]
2021
arXiv
pre-print
In this paper, we bring a new way of digesting news content by introducing the task of segmenting a news article into multiple sections and generating the corresponding summary to each section. We make two contributions towards this new task. First, we create and make available a dataset, SegNews, consisting of 27k news articles with sections and aligned heading-style section summaries. Second, we propose a novel segmentation-based language generation model adapted from pre-trained language
arXiv:2110.07850v1
fatcat:czteuaxppvdbfjyi2lg5kpki4y