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Multi-document summarization is a challenging task for which there existslittle large-scale datasets. We propose Multi-XScience, a large-scalemulti-document summarization dataset created from scientific articles.Multi-XScience introduces a challenging multi-document summarization task:writing the related-work section of a paper based on its abstract and thearticles it references. Our work is inspired by extreme summarization, adataset construction protocol that favours abstractive modeling approaches.Descriptive statistics and empirical results---using several state-of-the-artmodels trained on the Multi-XScience dataset---reveal that Multi-XScience iswell suited for abstractive models.

Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles