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Multi-document summarization (MDS) assumes a set of topic-related documents are provided as input.
The measurement of observer agreement for categorical data
J. Richard Landis and Gary G. Koch. 1977 · 1977
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Longformer: The long-document transformer
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A statistical interpretation of term specificity and its application in retrieval
Karen Spärck Jones. 2004 · 2004
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Evaluating content selection in summarization: The pyramid method
Ani Nenkova and Rebecca Passonneau. 2004 · 2004
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Ani Nenkova, Sameer Maskey, and Yang Liu. 2011 · 2011
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A bi-symmetric log transformation for wide-range data
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A sentence compression based framework to query-focused multi-document summarization
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Improving the estimation of word importance for news multi-document summarization
Kai Hong and Ani Nenkova. 2014 · 2014
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Ms marco: A human generated machine reading comprehension dataset
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Unsupervised query-focused multi-document summarization using the cross entropy method
Guy Feigenblat, Haggai Roitman, Odellia Boni, and David Konopnicki. 2017 · 2017
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Attention is all you need
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Graph-based neural multi-document summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
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Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
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Abstract Meaning Representation for multi-document summarization
Kexin Liao, Logan Lebanoff, and Fei Liu. 2018 · 2018
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Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer. 2018 · 2018
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Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir Radev. 2019 · 2019
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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
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Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Nlp augmentation
Edward Ma. 2019 · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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Perturbation sensitivity analysis to detect unintended model biases
Vinodkumar Prabhakaran, Ben Hutchinson, and Margaret Mitchell. 2019 · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
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A large-scale multi-document summarization dataset from the Wikipedia current events portal
Mitigating the position bias of transformer models in passage re-ranking
Sebastian Hofstätter, Aldo Lipani, Sophia Althammer, Markus Zlabinger, and Allan Hanbury. 2021 · 2021
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Datasets: A community library for natural language processing
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Evaluating the robustness of neural language models to input perturbations
Milad Moradi and Matthias Samwald. 2021 · 2021
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Data augmentation for abstractive query-focused multi-document summarization
Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, and Jianfeng Gao. 2021a · 2021
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Demian Gholipour Ghalandari, Chris Hokamp, Nghia The Pham, John Glover, and Georgiana Ifrim. 2020 · 2020
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Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
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Multi-granularity interaction network for extractive and abstractive multi-document summarization
Hanqi Jin, Tianming Wang, and Xiaojun Wan. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020b · 2020
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Leveraging graph to improve abstractive multi-document summarization
Wei Li, Xinyan Xiao, Jiachen Liu, Hua Wu, Haifeng Wang, and Junping Du. 2020 · 2020
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S2ORC: The semantic scholar open research corpus
Kyle Lo, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel Weld. 2020 · 2020
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Multi-XScience: A large-scale dataset for extreme multi-document summarization of scientific articles
Yao Lu, Yue Dong, and Laurent Charlin. 2020 · 2020
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Efficiently summarizing text and graph encodings of multi-document clusters
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KILT: a benchmark for knowledge intensive language tasks
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The expando-mono-duo design pattern for text ranking with pretrained sequence-to-sequence models
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Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
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Generating (factual?) narrative summaries of RCTs: Experiments with neural multi-document summarization
Byron C Wallace, Sayantan Saha, Frank Soboczenski, and Iain J Marshall. 2021 · 2021
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Demoting the lead bias in news summarization via alternating adversarial learning
Linzi Xing, Wen Xiao, and Giuseppe Carenini. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Scaling up query-focused summarization to meet open-domain question answering
Weijia Zhang, Svitlana Vakulenko, Thilina Rajapakse, and Evangelos Kanoulas. 2021 · 2021
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Improving language models by retrieving from trillions of tokens
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Lsg attention: Extrapolation of pretrained transformers to long sequences
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Re-examining system-level correlations of automatic summarization evaluation metrics
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Measuring faithfulness of abstractive summaries
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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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Deduplicating training data makes language models better
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Multi-lexsum: Real-world summaries of civil rights lawsuits at multiple granularities
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Pyterrier sentence transformers
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How “multi” is multi-document summarization?
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PRIMERA: Pyramid-based masked sentence pre-training for multi-document summarization
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