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Sentence centrality revisited for unsupervised summarization
Original
Hao Zheng and Mirella Lapata. 2019 · 1906
Earlier work this paper cites.
Text summarization with pretrained encoders
Original
Yang Liu and Mirella Lapata. 2019 · 1908
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Original
Nils Reimers and Iryna Gurevych. 2019 · 1908
Earlier work this paper cites.
On extractive and abstractive neural document summarization with transformer language models
Original
Sandeep Subramanian, Raymond Li, Jonathan Pilault, and Christopher Pal. 2019 · 1909
Earlier work this paper cites.
Extractive summarization of long documents by combining global and local context
Original
Wen Xiao and Giuseppe Carenini. 2019 · 1909
Earlier work this paper cites.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Original
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
Discourse-aware neural extractive model for text summarization
Original
Jiacheng Xu, Zhe Gan, Yu Cheng, and Jingjing Liu. 2019 · 1910
Earlier work this paper cites.
The structure of a scientific paper
Frederick Suppe. 1998 · 1998
Earlier work this paper cites.
Graph-bert: Only attention is needed for learning graph representations
Original
Jiawei Zhang, Haopeng Zhang, Li Sun, and Congying Xia. 2020 · 2001
Earlier work this paper cites.
Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
Earlier work this paper cites.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
Earlier work this paper cites.
Longformer: The long-document transformer
Original
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.
Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R Radev. 2004 · 2004
Earlier work this paper cites.
Centroid-based summarization of multiple documents
Dragomir R Radev, Hongyan Jing, Małgorzata Styś, and Daniel Tam. 2004 · 2004
Earlier work this paper cites.

Similar

Heterogeneous graph neural networks for extractive document summarization
Original
Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, and Xuanjing Huang. 2020 · 2004
Cited alongside, same era.
Discourse-aware unsupervised summarization of long scientific documents
Original
Yue Dong, Andrei Mircea, and Jackie CK Cheung. 2020 · 2005
Cited alongside, same era.
The new york times annotated corpus
Evan Sandhaus. 2008 · 2008
Cited alongside, same era.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
Cited alongside, same era.
Enhancing extractive text summarization with topic-aware graph neural networks
Original
Peng Cui, Le Hu, and Yuanchao Liu. 2020 · 2010
Cited alongside, same era.

Then

Graph-based neural multi-document summarization
Original
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
Later among the works it cites.
A discourse-aware attention model for abstractive summarization of long documents
Original
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Original
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
Ranking sentences for extractive summarization with reinforcement learning
Original
Shashi Narayan, Shay B Cohen, and Mirella Lapata. 2018 · 2018
Later among the works it cites.

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2022

HEGEL: Hypergraph Transformer for Long Document Summarization

Zhang, Haopeng, Liu, Xiao, Zhang, Jiawei

Understand

Extractive summarization for long documents is challenging due to the extended structured input context.

The long-distance sentence dependency hinders cross-sentence relations modeling, the critical step of extractive summarization.
This paper proposes HEGEL, a hypergraph neural network for long document summarization by capturing high-order cross-sentence relations.
HEGEL updates and learns effective sentence representations with hypergraph transformer layers and fuses different types of sentence dependencies, including latent topics, keywords coreference, and section structure.

Built on

Sentence centrality revisited for unsupervised summarization
Original
Hao Zheng and Mirella Lapata. 2019 · 1906
Earlier work this paper cites.
Text summarization with pretrained encoders
Original
Yang Liu and Mirella Lapata. 2019 · 1908
Earlier work this paper cites.
Sentence-bert: Sentence embeddings using siamese bert-networks
Original
Nils Reimers and Iryna Gurevych. 2019 · 1908
Earlier work this paper cites.
On extractive and abstractive neural document summarization with transformer language models
Original
Sandeep Subramanian, Raymond Li, Jonathan Pilault, and Christopher Pal. 2019 · 1909
Earlier work this paper cites.
Extractive summarization of long documents by combining global and local context
Original
Wen Xiao and Giuseppe Carenini. 2019 · 1909
Earlier work this paper cites.
Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Original
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
Discourse-aware neural extractive model for text summarization
Original
Jiacheng Xu, Zhe Gan, Yu Cheng, and Jingjing Liu. 2019 · 1910
Earlier work this paper cites.
The structure of a scientific paper
Frederick Suppe. 1998 · 1998
Earlier work this paper cites.
Graph-bert: Only attention is needed for learning graph representations
Original
Jiawei Zhang, Haopeng Zhang, Li Sun, and Congying Xia. 2020 · 2001
Earlier work this paper cites.
Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
Earlier work this paper cites.
Automatic evaluation of summaries using n-gram co-occurrence statistics
Chin-Yew Lin and Eduard Hovy. 2003 · 2003
Earlier work this paper cites.
Longformer: The long-document transformer
Original
Iz Beltagy, Matthew E Peters, and Arman Cohan. 2020 · 2004
Earlier work this paper cites.
Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R Radev. 2004 · 2004
Earlier work this paper cites.
Centroid-based summarization of multiple documents
Dragomir R Radev, Hongyan Jing, Małgorzata Styś, and Daniel Tam. 2004 · 2004
Earlier work this paper cites.

Similar

Heterogeneous graph neural networks for extractive document summarization
Original
Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, and Xuanjing Huang. 2020 · 2004
Cited alongside, same era.
Discourse-aware unsupervised summarization of long scientific documents
Original
Yue Dong, Andrei Mircea, and Jackie CK Cheung. 2020 · 2005
Cited alongside, same era.
The new york times annotated corpus
Evan Sandhaus. 2008 · 2008
Cited alongside, same era.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
Cited alongside, same era.
Enhancing extractive text summarization with topic-aware graph neural networks
Original
Peng Cui, Le Hu, and Yuanchao Liu. 2020 · 2010
Cited alongside, same era.

Then

Graph-based neural multi-document summarization
Original
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
Later among the works it cites.
A discourse-aware attention model for abstractive summarization of long documents
Original
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, and Nazli Goharian. 2018 · 2018
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
Original
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
Later among the works it cites.
Ranking sentences for extractive summarization with reinforcement learning
Original
Shashi Narayan, Shay B Cohen, and Mirella Lapata. 2018 · 2018
Later among the works it cites.

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Be more with less: Hypergraph attention networks for inductive text classification

Original

Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, and Huan Liu. 2020 · 2011

Cited alongside, same era.

Systematically exploring redundancy reduction in summarizing long documents

Original

Wen Xiao and Giuseppe Carenini. 2020 · 2012

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Domain-independent abstract generation for focused meeting summarization

Lu Wang and Claire Cardie. 2013 · 2013

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Teaching machines to read and comprehend

Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015

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Neural summarization by extracting sentences and words

Original

Jianpeng Cheng and Mirella Lapata. 2016 · 2016

Cited alongside, same era.

Decoupled weight decay regularization

Original

Ilya Loshchilov and Frank Hutter. 2017 · 2017

Cited alongside, same era.

Get to the point: Summarization with pointer-generator networks

Original

Abigail See, Peter J Liu, and Christopher D Manning. 2017 · 2017

Cited alongside, same era.

AUTH @ CLSciSumm 20, LaySumm 20, LongSumm 20

Alexios Gidiotis, Stefanos Stefanidis, and Grigorios Tsoumakas. 2020 · 2020