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Found 11 papers, 7 papers with code
CNewSum: A Large-scale Chinese News Summarization Dataset with Human-annotated Adequacy and Deducibility Level
In this paper, we present a large-scale Chinese news summarization dataset CNewSum, which consists of 304, 307 documents and human-written summaries for the news feed.
Generating Antimicrobial Peptides from Latent Secondary Structure Space
By sampling in the latent secondary structure space, we can generate peptides with ideal amino acids and secondary structures at the same time.
MTG: A Benchmark Suite for Multilingual Text Generation
We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation.
Enhancing Scientific Papers Summarization with Citation Graph
Previous work for text summarization in scientific domain mainly focused on the content of the input document, but seldom considering its citation network.
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems
In this paper, we perform an in-depth analysis of characteristics of different datasets and investigate the performance of different summarization models under a cross-dataset setting, in which a summarizer trained on one corpus will be evaluated on a range of out-of-domain corpora.
Heterogeneous Graph Neural Networks for Extractive Document Summarization
An intuitive way is to put them in the graph-based neural network, which has a more complex structure for capturing inter-sentence relationships.
Extractive Summarization as Text Matching
This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems.
Ranked #1 on
Text Summarization
on BBC XSum
A Closer Look at Data Bias in Neural Extractive Summarization Models
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 extractive summarization models.
Exploring Domain Shift in Extractive Text Summarization
Although domain shift has been well explored in many NLP applications, it still has received little attention in the domain of extractive text summarization.
Searching for Effective Neural Extractive Summarization: What Works and What's Next
The recent years have seen remarkable success in the use of deep neural networks on text summarization.
Ranked #6 on
Extractive Text Summarization
on CNN / Daily Mail
