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Like humans, document summarization models can interpret a document's contents in a number of ways.
Sentence Centrality Revisited for Unsupervised Summarization
Zheng, H.; and Lapata, M. 2019 · 1906
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Text summarization with pretrained encoders
Liu, Y.; and Lapata, M. 2019 · 1908
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An Entity-Driven Framework for Abstractive Summarization
Sharma, E.; Huang, L.; Hu, Z.; and Wang, L. 2019 · 1909
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Generalization through Memorization: Nearest Neighbor Language Models
Khandelwal, U.; Levy, O.; Jurafsky, D.; Zettlemoyer, L.; and Lewis, M. 2019 · 1911
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Towards a functional theory of text organization
Mann, W. C.; and Thompson, S. A. 1988 · 1988
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Rouge: A package for automatic evaluation of summaries
Lin, C.-Y. 2004 · 2004
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Textrank: Bringing order into text
Mihalcea, R.; and Tarau, P. 2004 · 2004
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On Faithfulness and Factuality in Abstractive Summarization
Maynez, J.; Narayan, S.; Bohnet, B.; and McDonald, R. 2020 · 2005
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Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints
Durrett, G.; Berg-Kirkpatrick, T.; and Klein, D. 2016 · 2008
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The new york times annotated corpus
Sandhaus, E. 2008 · 2008
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Discourse Constraints for Document Compression
Clarke, J.; and Lapata, M. 2010 · 2010
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The Stanford CoreNLP Natural Language Processing Toolkit
Manning, C. D.; Surdeanu, M.; Bauer, J.; Finkel, J.; Bethard, S. J.; and McClosky, D. 2014 · 2014
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Teaching machines to read and comprehend
Hermann, K. M.; Kocisky, T.; Grefenstette, E.; Espeholt, L.; Kay, W.; Suleyman, M.; and Blunsom, P. 2015 · 2015
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Pointer networks
Vinyals, O.; Fortunato, M.; and Jaitly, N. 2015 · 2015
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Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond
Nallapati, R.; Zhou, B.; dos Santos, C. N.; Gülçehre, Ç.; and Xiang, B. 2016 · 2016
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Szegedy, C.; Vanhoucke, V.; Ioffe, S.; Shlens, J.; and Wojna, Z. 2016 · 2016
Cited alongside, same era.
Summarunner: A recurrent neural network based sequence model for extractive summarization of documents
Nallapati, R.; Zhai, F.; and Zhou, B. 2017 · 2017
Cited alongside, same era.
A Deep Reinforced Model for Abstractive Summarization
Paulus, R.; Xiong, C.; and Socher, R. 2017 · 2017
Cited alongside, same era.
Get To The Point: Summarization with Pointer-Generator Networks
See, A.; Liu, P. J.; and Manning, C. D. 2017 · 2017
Cited alongside, same era.
Abstractive document summarization with a graph-based attentional neural model
A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss
Hsu, W.-T.; Lin, C.-K.; Lee, M.-Y.; Min, K.; Tang, J.; and Sun, M. 2018 · 2018
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Improving neural abstractive document summarization with explicit information selection modeling
Li, W.; Xiao, X.; Lyu, Y.; and Wang, Y. 2018 · 2018
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Ranking Sentences for Extractive Summarization with Reinforcement Learning
Narayan, S.; Cohen, S. B.; and Lapata, M. 2018 · 2018
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Deep contextualized word representations
Peters, M. E.; Neumann, M.; Iyyer, M.; Gardner, M.; Clark, C.; Lee, K.; and Zettlemoyer, L. 2018 · 2018
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Improving language understanding by generative pre-training
Radford, A.; Narasimhan, K.; Salimans, T.; and Sutskever, I. 2018 · 2018
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Tan, J.; Wan, X.; and Xiao, J. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
Cited alongside, same era.
Selective Encoding for Abstractive Sentence Summarization
Zhou, Q.; Yang, N.; Wei, F.; and Zhou, M. 2017 · 2017
Cited alongside, same era.
Deep Communicating Agents for Abstractive Summarization
Celikyilmaz, A.; Bosselut, A.; He, X.; and Choi, Y. 2018 · 2018
Cited alongside, same era.
Deep Communicating Agents for Abstractive Summarization
Çelikyilmaz, A.; Bosselut, A.; He, X.; and Choi, Y. 2018 · 2018
Cited alongside, same era.
Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting
Chen, Y.-C.; and Bansal, M. 2018 · 2018
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
Cited alongside, same era.
Neural Document Summarization by Jointly Learning to Score and Select Sentences
Zhou, Q.; Yang, N.; Wei, F.; Huang, S.; Zhou, M.; and Zhao, T. 2018 · 2018
Later among the works it cites.
Mixture Content Selection for Diverse Sequence Generation
Cho, J.; Seo, M.; and Hajishirzi, H. 2019 · 2019
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A simple theoretical model of importance for summarization
Peyrard, M. 2019 · 2019
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Select and Attend: Towards Controllable Content Selection in Text Generation
Shen, X.; Suzuki, J.; Inui, K.; Su, H.; Klakow, D.; and Sekine, S. 2019 · 2019
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Concept Pointer Network for Abstractive Summarization
Wang, W.; Gao, Y.; Huang, H.-Y.; and Zhou, Y. 2019 · 2019
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BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis
Xu, H.; Liu, B.; Shu, L.; and Yu, P. 2019 · 2019
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Improving Abstractive Document Summarization with Salient Information Modeling
You, Y.; Jia, W.; Liu, T.; and Yang, W. 2019 · 2019
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HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization
Zhang, X.; Wei, F.; and Zhou, M. 2019 · 2019
Later among the works it cites.