Multi-News: a Large-Scale Multi-Document Summarization
Dataset and Abstractive Hierarchical Model
Abstract
Automatic generation of summaries from multiple news articles is a valuable tool as the
number of online publications grows rapidly.
Single document summarization (SDS) systems have benefited from advances in neural encoder-decoder model thanks to the availability of large datasets. However, multidocument summarization (MDS) of news articles has been limited to datasets of a couple
of hundred examples. In this paper, we introduce Multi-News, the first large-scale MDS
news dataset. Additionally, we propose an
end-to-end model which incorporates a traditional extractive summarization model with a
standard SDS model and achieves competitive
results on MDS datasets. We benchmark several methods on Multi-News and release our
data and code in hope that this work will promote advances in summarization in the multidocument setting