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Open-domain Multi-Document Summarization (ODMDS) is a critical tool for condensing vast arrays of documents into coherent, concise summaries.
Okapi at trec-3
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Timo Schick and Hinrich Schütze. 2020 · 2009
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Aquamuse: Automatically generating datasets for query-based multi-document summarization
Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, and Eugene Ie. 2020 · 2010
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Open-domain multi-document summarization via information extraction: Challenges and prospects
Heng Ji, Benoit Favre, Wen-Pin Lin, Daniel Gillick, Dilek Z. Hakkani-Tür, and Ralph Grishman. 2013 · 2013
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Graph-based neural multi-document summarization
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Yi Yang, Wen-tau Yih, and Christopher Meek. 2015 · 2018
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Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
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Hierarchical transformers for multi-document summarization
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Decoupled weight decay regularization
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Improving document representations by generating pseudo query embeddings for dense retrieval
Palm: Scaling language modeling with pathways
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News summarization and evaluation in the era of gpt-3
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Unsupervised dense information retrieval with contrastive learning
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