Corpus ID: 235352668

AgreeSum: Agreement-Oriented Multi-Document Summarization

@inproceedings{Pang2021AgreeSumAM,
  title={AgreeSum: Agreement-Oriented Multi-Document Summarization},
  author={Richard Yuanzhe Pang and {\'A}. Lelkes and Vinh Q. Tran and Cong Yu},
  booktitle={FINDINGS},
  year={2021}
}
We aim to renew interest in a particular multidocument summarization (MDS) task which we call AgreeSum: agreement-oriented multidocument summarization. Given a cluster of articles, the goal is to provide abstractive summaries that represent information common and faithful to all input articles. Given the lack of existing datasets, we create a dataset for AgreeSum, and provide annotations on article-summary entailment relations for a subset of the clusters in the dataset. We aim to create strong… Expand

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References

SHOWING 1-10 OF 57 REFERENCES
Abstractive Unsupervised Multi-Document Summarization using Paraphrastic Sentence Fusion
Leveraging Graph to Improve Abstractive Multi-Document Summarization
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
Evaluating the Factual Consistency of Abstractive Text Summarization
SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders
Heterogeneous Graph Neural Networks for Extractive Document Summarization
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