38 citations · 189 across the 27 of their papers we have counts for
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cs.CL2019★ 7 cited
A Closer Look at Data Bias in Neural Extractive Summarization Models
Ming Zhong, Danqing Wang, Pengfei Liu +2
In this paper, we take stock of the current state of summarization datasets and explore how different factors of datasets influence the generalization behaviour of neural extractiv…
cs.CL2019★ 38 cited
Exploring Domain Shift in Extractive Text Summarization
Danqing Wang, Pengfei Liu, Ming Zhong +3
Although domain shift has been well explored in many NLP applications, it still has received little attention in the domain of extractive text summarization. As a result, the model…
cs.CL2019★ 20 cited
Searching for Effective Neural Extractive Summarization: What Works and What's Next
Ming Zhong, Pengfei Liu, Danqing Wang +2
The recent years have seen remarkable success in the use of deep neural networks on text summarization. However, there is no clear understanding of \textit{why} they perform so wel…