Papers › Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive...

Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model

4 Jun 2019ACL 2019 7arXiv:1906.01749archive 2025-07-28

Alexander R. Fabbri, Irene Li, Tianwei She, Suyi Li, Dragomir R. Radev

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, multi-document 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 multi-document setting.

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Tasks

ArticlesDecoderDocument SummarizationExtractive SummarizationMulti-Document Summarization

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Multi-News

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Multi-Document Summarization Multi-News Hi-MAP ROUGE-1 43.47 #5 of 6 Archive leaderboard report
Multi-Document Summarization Multi-News Hi-MAP ROUGE-2 14.89 #5 of 6 Archive leaderboard report
Multi-Document Summarization Multi-News Hi-MAP ROUGE-SU4 17.41 #5 of 6 Archive leaderboard report

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