id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-122344-2lepkvby	Hayashi, Hiroaki	What's New? Summarizing Contributions in Scientific Literature	2020-11-06		.txt	text/plain	7260	383	44	To overcome this problem, we introduce a new task of disentangled paper summarization, which seeks to generate separate summaries for the paper contributions and the context of the work, making it easier to identify the key findings shared in articles. The new task's goal is to generate two summaries simultaneously, one strictly focused on the summarized article's novelties and contributions, the other introducing the context of the work and previous efforts. Recent trends in abstractive text summarization show a shift of focus from designing task-specific architectures trained from scratch (See et al., 2017; Paulus et al., 2018) to leveraging large-scale Transformer-based models pre-trained on vast amounts of data (Liu & Lapata, 2019; Lewis et al., 2020) , often in multi-task settings (Raffel et al., 2019) . In this paper, we propose disentangled paper summarization, a new task in scientific paper summarizing where models simultaneously generate contribution and context summaries.	./cache/cord-122344-2lepkvby.txt	./txt/cord-122344-2lepkvby.txt