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

Yue Dong, Yao Lu, Laurent Charlin

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Abstract

Multi-document summarization is a challenging task for which there exists little largescale datasets. We propose Multi-XScience, a large-scale multi-document summarization dataset created from scientific articles. Multi-XScience introduces a challenging multidocument summarization task: writing the related-work section of a paper based on its abstract and the articles it references. Our work is inspired by extreme summarization, a dataset construction protocol that favours abstractive modeling approaches. Descriptive statistics and empirical results-using several state-of-the-art models trained on the Multi-XScience dataset-reveal that Multi-XScience is well suited for abstractive models. 1

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