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Large language models have shown impressive performance across a wide variety of tasks, including text summarization.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D 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 Ziegler, Jeffrey Wu, Clemens Winter, Chris 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 · 1901
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WordNet: A lexical database for English
George A. Miller. 1994 · 1994
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Nltk: The natural language toolkit
Edward Loper and Steven Bird. 2002 · 2002
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Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R. Radev. 2004 · 2004
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Multi-document summarization of evaluative text
Giuseppe Carenini, Raymond Ng, and Adam Pauls. 2006 · 2006
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Opinion extraction, summarization and tracking in news and blog corpora
Lun-Wei Ku, Yu-Ting Liang, and Hsin-Hsi Chen. 2006 · 2006
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Correlation between ROUGE and human evaluation of extractive meeting summaries
Feifan Liu and Yang Liu. 2008 · 2008
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Opinosis: A graph based approach to abstractive summarization of highly redundant opinions
Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010 · 2010
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Summarizing contrastive viewpoints in opinionated text
Michael Paul, ChengXiang Zhai, and Roxana Girju. 2010 · 2010
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A hybrid approach to multi-document summarization of opinions in reviews
Giuseppe Di Fabbrizio, Amanda Stent, and Robert Gaizauskas. 2014 · 2014
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Revisiting summarization evaluation for scientific articles
Arman Cohan and Nazli Goharian. 2016 · 2016
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Summarizing opinions: Aspect extraction meets sentiment prediction and they are both weakly supervised
Stefanos Angelidis and Mirella Lapata. 2018 · 2018
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Fast abstractive summarization with reinforce-selected sentence rewriting
Yen-Chun Chen and Mohit Bansal. 2018 · 2018
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Bottom-up abstractive summarization
Sebastian Gehrmann, Yuntian Deng, and Alexander Rush. 2018 · 2018
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Structure-infused copy mechanisms for abstractive summarization
Kaiqiang Song, Lin Zhao, and Fei Liu. 2018 · 2018
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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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Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
Cited alongside, same era.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019a · 2019
Cited alongside, same era.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019b · 2019
Cited alongside, same era.
The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2019 · 2019
Cited alongside, same era.
Universal adversarial triggers for attacking and analyzing NLP
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 2019
Cited alongside, same era.
Few-shot learning for opinion summarization
Arthur Bražinskas, Mirella Lapata, and Ivan Titov. 2020a · 2020
Cited alongside, same era.
BiSECT: Learning to split and rephrase sentences with bitexts
Joongwon Kim, Mounica Maddela, Reno Kriz, Wei Xu, and Chris Callison-Burch. 2021 · 2021
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Considering nested tree structure in sentence extractive summarization with pre-trained transformer
Jingun Kwon, Naoki Kobayashi, Hidetaka Kamigaito, and Manabu Okumura. 2021 · 2021
Later among the works it cites.
EASE: Extractive-abstractive summarization end-to-end using the information bottleneck principle
Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, and Marjan Ghazvininejad. 2021 · 2021
Later among the works it cites.
Gender and representation bias in GPT-3 generated stories
Li Lucy and David Bamman. 2021 · 2021
Later among the works it cites.
QuestEval: Summarization asks for fact-based evaluation
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano, Alex Wang, and Patrick Gallinari. 2021 · 2021
Later among the works it cites.
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CTRLsum: Towards Generic Controllable Text Summarization
Junxian He, Wojciech Kryściński, Bryan McCann, Nazneen Rajani, and Caiming Xiong. 2020 · 2020
Cited alongside, same era.
Neural extractive summarization with hierarchical attentive heterogeneous graph network
Ruipeng Jia, Yanan Cao, Hengzhu Tang, Fang Fang, Cong Cao, and Shi Wang. 2020 · 2020
Cited alongside, same era.
Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
Cited alongside, same era.
BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
“you are grounded!”: Latent name artifacts in pre-trained language models
Vered Shwartz, Rachel Rudinger, and Oyvind Tafjord. 2020 · 2020
Cited alongside, same era.
Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020b · 2020
Cited alongside, same era.
Jeff Wu, Long Ouyang, Daniel M. Ziegler, Nisan Stiennon, Ryan Lowe, Jan Leike, and Paul Christiano. 2021 · 2021
Later among the works it cites.
ASPECTNEWS: Aspect-oriented summarization of news documents
Ojas Ahuja, Jiacheng Xu, Akshay Gupta, Kevin Horecka, and Greg Durrett. 2022 · 2022
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NEWTS: A corpus for news topic-focused summarization
Seyed Ali Bahrainian, Sheridan Feucht, and Carsten Eickhoff. 2022 · 2022
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GLM: General language model pretraining with autoregressive blank infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang. 2022 · 2022
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Repairing the cracked foundation: A survey of obstacles in evaluation practices for generated text
Sebastian Gehrmann, Elizabeth Clark, and Thibault Sellam. 2022 · 2022
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News Summarization and Evaluation in the Era of GPT-3
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
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MemSum: Extractive summarization of long documents using multi-step episodic Markov decision processes
Nianlong Gu, Elliott Ash, and Richard Hahnloser. 2022 · 2022
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SummaC: Re-visiting NLI-based models for inconsistency detection in summarization
Philippe Laban, Tobias Schnabel, Paul N. Bennett, and Marti A. Hearst. 2022 · 2022
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Faithful or extractive? on mitigating the faithfulness-abstractiveness trade-off in abstractive summarization
Faisal Ladhak, Esin Durmus, He He, Claire Cardie, and Kathleen McKeown. 2022 · 2022
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SummaReranker: A multi-task mixture-of-experts re-ranking framework for abstractive summarization
Mathieu Ravaut, Shafiq Joty, and Nancy Chen. 2022 · 2022
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Self-critiquing models for assisting human evaluators
William Saunders, Catherine Yeh, Jeff Wu, Steven Bills, Long Ouyang, Jonathan Ward, and Jan Leike. 2022 · 2022
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Oasum: Large-scale open domain aspect-based summarization
Xianjun Yang, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Xiaoman Pan, Linda Petzold, and Dong Yu. 2022 · 2022
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Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors
Liyan Tang, Tanya Goyal, Alexander R. Fabbri, Philippe Laban, Jiacheng Xu, Semih Yahvuz, Wojciech Kryściński, Justin F. Rousseau, and Greg Durrett. 2023 · 2023
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Towards a unified multi-dimensional evaluator for text generation
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han. 2022 · 2038
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