Corpus ID: 225067629

AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization

@article{Kulkarni2020AQuaMuSeAG,
  title={AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization},
  author={Sayali Kulkarni and Sheide Chammas and Wan Zhu and Fei Sha and Eugene Ie},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.12694}
}
Summarization is the task of compressing source document(s) into coherent and succinct passages. This is a valuable tool to present users with concise and accurate sketch of the top ranked documents related to their queries. Query-based multi-document summarization (qMDS) addresses this pervasive need, but the research is severely limited due to lack of training and evaluation datasets as existing single-document and multi-document summarization datasets are inadequate in form and scale. We… Expand

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