37 citations · 88 across the 5 of their papers we have counts for
7 papers · 1 filter
Enhancing Scientific Papers Summarization with Citation Graph
Chenxin An, Ming Zhong, Yiran Chen +3
Previous work for text summarization in scientific domain mainly focused on the content of the input document, but seldom considering its citation network. However, scientific pape…
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems
Yiran Chen, Pengfei Liu, Ming Zhong +4
Neural network-based models augmented with unsupervised pre-trained knowledge have achieved impressive performance on text summarization. However, most existing evaluation methods…
Heterogeneous Graph Neural Networks for Extractive Document Summarization
Danqing Wang, Pengfei Liu, Yining Zheng +2
As a crucial step in extractive document summarization, learning cross-sentence relations has been explored by a plethora of approaches. An intuitive way is to put them in the grap…
Extractive Summarization as Text Matching
Ming Zhong, Pengfei Liu, Yiran Chen +3
This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems. Instead of following the commonly used framework of extracting sentence…
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…
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…