mlsanityData to 7 Oct 2026

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

arXiv 1906.01749 ↗First posted 4 Jun 2019cs.CLcited by 431

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Cited by 51 in Efficient LLM inference and serving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

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.

Key facts. Cited by 431 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Jun 2019.

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Citing papers per year: 2021: 66; 2022: 54; 2023: 73; 2024: 96; 2025: 84; 2026: 58.

431 papers.

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