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Aspect-based summarization is the task of generating focused summaries based on specific points of interest.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R’emi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
Earlier work this paper cites.
ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
TextRank: Bringing order into text
Rada Mihalcea and Paul Tarau. 2004 · 2004
Earlier work this paper cites.
A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization
Ani Nenkova, Lucy Vanderwende, and Kathleen McKeown. 2006 · 2006
Earlier work this paper cites.
Dbpedia: A nucleus for a web of open data
Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007 · 2007
Earlier work this paper cites.
A Joint Model of Text and Aspect Ratings for Sentiment Summarization
Ivan Titov and Ryan McDonald. 2008 · 2008
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Rated aspect summarization of short comments
Yue Lu, ChengXiang Zhai, and Neel Sundaresan. 2009 · 2009
Earlier work this paper cites.
Automatically Generating Wikipedia Articles: A Structure-Aware Approach
Christina Sauper and Regina Barzilay. 2009 · 2009
Earlier work this paper cites.
Ranking with recursive neural networks and its application to multi-document summarization
Ziqiang Cao, Furu Wei, Li Dong, Sujian Li, and Ming Zhou. 2015 · 2015
Earlier work this paper cites.
Movie script summarization as graph-based scene extraction
Philip John Gorinski and Mirella Lapata. 2015 · 2015
Cited alongside, same era.
Variations of the similarity function of textrank for automated summarization
Federico Barrios, Federico López, Luis Argerich, and Rosa Wachenchauzer. 2016 · 2016
Cited alongside, same era.
Abstractive text summarization using sequence-to-sequence RNNs and beyond
Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çağlar Gulçehre, and Bing Xiang. 2016 · 2016
Cited alongside, same era.
Neural Network-Based Abstract Generation for Opinions and Arguments
Lu Wang and Wang Ling. 2016 · 2016
Cited alongside, same era.
Graph-based Neural Multi-Document Summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
Cited alongside, same era.
Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization
Logan Lebanoff, Kaiqiang Song, 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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Aspect and sentiment aware abstractive review summarization
Min Yang, Qiang Qu, Ying Shen, Qiao Liu, Wei Zhao, and Jia Zhu. 2018 · 2018
Later among the works it cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
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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Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised
Stefanos Angelidis and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
Cited alongside, same era.
A dataset of peer reviews (PeerRead): Collection, insights and NLP applications
Dongyeop Kang, Waleed Ammar, Bhavana Dalvi, Madeleine van Zuylen, Sebastian Kohlmeier, Eduard Hovy, and Roy Schwartz. 2018 · 2018
Cited alongside, same era.
Content selection in deep learning models of summarization
Chris Kedzie, Kathleen McKeown, and Hal Daumé III. 2018 · 2018
Cited alongside, same era.
Generating Topic-Oriented Summaries Using Neural Attention
Kundan Krishna and Balaji Vasan Srinivasan. 2018 · 2018
Cited alongside, same era.
Hierarchical transformers for multi-document summarization
Yang Liu and Mirella Lapata. 2019a
Cited in the paper.
Using local knowledge graph construction to scale Seq2Seq models to multi-document inputs
Angela Fan, Claire Gardent, Chloé Braud, and Antoine Bordes. 2019 · 2019
Later among the works it cites.
Inducing Document Structure for Aspect-based Summarization
Lea Frermann and Alexandre Klementiev. 2019 · 2019
Later among the works it cites.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019b · 2019
Later among the works it cites.
Generating Summaries with Topic Templates and Structured Convolutional Decoders
Laura Perez-Beltrachini, Yang Liu, and Mirella Lapata. 2019 · 2019
Later among the works it cites.