15 citations · 34 across the 16 of their papers we have counts for
Showing 2020Show all
2 papers · 1 filter
cs.CL2020
Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help !
Wen Xiao, Patrick Huber, Giuseppe Carenini
The multi-head self-attention of popular transformer models is widely used within Natural Language Processing (NLP), including for the task of extractive summarization. With the go…
cs.CL2020★ 15 cited
Systematically Exploring Redundancy Reduction in Summarizing Long Documents
Wen Xiao, Giuseppe Carenini
Our analysis of large summarization datasets indicates that redundancy is a very serious problem when summarizing long documents. Yet, redundancy reduction has not been thoroughly…