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Much of modern-day text simplification research focuses on sentence-level simplification, transforming original, more complex sentences into simplified versions.
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, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
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The measurement of observer agreement for categorical data
J Richard Landis and Gary G Koch. 1977 · 1977
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Reading comprehension and readability in educational practice and psychological theory
Walter Kintsch and Douglas Vipond. 1985 · 1985
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The effects of simplified and elaborated texts on foreign language reading comprehension
Yasukata Yano, Michael H Long, and Steven Ross. 1994 · 1994
Earlier work this paper cites.
Practical simplification of english newspaper text to assist aphasic readers
John Carroll, Guido Minnen, Yvonne Canning, Siobhan Devlin, and John Tait. 1998 · 1998
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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SIMTEXT: Text simplification of medical literature
Jerwin Jan S Damay, Gerard Jaime D Lojico, Kimberly Amanda L Lu, D Tarantan, and E Ong. 2006 · 2006
Earlier work this paper cites.
Measuring agreement on set-valued items (MASI) for semantic and pragmatic annotation
Rebecca Passonneau. 2006 · 2006
Earlier work this paper cites.
Text simplification for language learners: a corpus analysis
Sarah E Petersen and Mari Ostendorf. 2007 · 2007
Earlier work this paper cites.
Beyond sumbasic: Task-focused summarization with sentence simplification and lexical expansion
Lucy Vanderwende, Hisami Suzuki, Chris Brockett, and Ani Nenkova. 2007 · 2007
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Inter-coder agreement for computational linguistics
Ron Artstein and Massimo Poesio. 2008 · 2008
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Text simplification for children
Jan De Belder and Marie-Francine Moens. 2010 · 2010
Earlier work this paper cites.
A semantic and syntactic text simplification tool for health content
Sasikiran Kandula, Dorothy Curtis, and Qing Zeng-Treitler. 2010 · 2010
Earlier work this paper cites.
A monolingual tree-based translation model for sentence simplification
Zhemin Zhu, Delphine Bernhard, and Iryna Gurevych. 2010 · 2010
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Simple English Wikipedia: A new text simplification task
William Coster and David Kauchak. 2011 · 2011
Earlier work this paper cites.
Learning to simplify sentences with quasi-synchronous grammar and integer programming
Kristian Woodsend and Mirella Lapata. 2011 · 2011
Earlier work this paper cites.
A simplification-translation-restoration framework for cross-domain SMT applications
Han-Bin Chen, Hen-Hsen Huang, Hsin-Hsi Chen, and Ching-Ting Tan. 2012 · 2012
Earlier work this paper cites.
Sense-specific lexical information for reading assistance
Soojeong Eom, Markus Dickinson, and Rebecca Sachs. 2012 · 2012
Earlier work this paper cites.
Enhancing multi-document summaries with sentence simplification
Sara Botelho Silveira and António Branco. 2012 · 2012
Cited alongside, same era.
Sentence simplification by monolingual machine translation
Sander Wubben, Antal van den Bosch, and Emiel Krahmer. 2012 · 2012
Cited alongside, same era.
Selecting proper lexical paraphrase for children
Tomoyuki Kajiwara, Hiroshi Matsumoto, and Kazuhide Yamamoto. 2013 · 2013
Cited alongside, same era.
Frequent words improve readability and short words improve understandability for people with dyslexia
Luz Rello, Ricardo Baeza-Yates, Laura Dempere-Marco, and Horacio Saggion. 2013 · 2013
Cited alongside, same era.
An open corpus of everyday documents for simplification tasks
David Pellow and Maxine Eskenazi. 2014 · 2014
Cited alongside, same era.
A survey of research on text simplification
Advaith Siddharthan. 2014 · 2014
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
Later among the works it cites.
A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature
Benjamin Nye, Junyi Jessy Li, Roma Patel, Yinfei Yang, Iain Marshall, Ani Nenkova, and Byron Wallace. 2018 · 2018
Later among the works it cites.
Unsupervised learning of sentence embeddings using compositional n-gram features
Matteo Pagliardini, Prakhar Gupta, and Martin Jaggi. 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
Later among the works it cites.
EditNTS: An neural programmer-interpreter model for sentence simplification through explicit editing
Yue Dong, Zichao Li, Mehdi Rezagholizadeh, and Jackie Chi Kit Cheung. 2019 · 2019
Later among the works it cites.
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Cited alongside, same era.
Problems in current text simplification research: New data can help
Wei Xu, Chris Callison-Burch, and Courtney Napoles. 2015 · 2015
Cited alongside, same era.
Improving the annotation of sentence specificity
Junyi Jessy Li, Bridget O’Daniel, Yi Wu, Wenli Zhao, and Ani Nenkova. 2016 · 2016
Cited alongside, same era.
How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
Chia-Wei Liu, Ryan Lowe, Iulian Serban, Mike Noseworthy, Laurent Charlin, and Joelle Pineau. 2016 · 2016
Cited alongside, same era.
Anita: An intelligent text adaptation tool
Gustavo Paetzold and Lucia Specia. 2016 · 2016
Cited alongside, same era.
Lexical Simplification for Non-Native English Speakers
Gustavo Henrique Paetzold. 2016 · 2016
Cited alongside, same era.
Can text simplification help machine translation?
Sanja Štajner and Maja Popovic. 2016 · 2016
Cited alongside, same era.
PoMo: Generating entity-specific post-modifiers in context
Jun Seok Kang, Robert Logan, Zewei Chu, Yang Chen, Dheeru Dua, Kevin Gimpel, Sameer Singh, and Niranjan Balasubramanian. 2019 · 2019
Later among the works it cites.
Domain agnostic real-valued specificity prediction
Wei-Jen Ko, Greg Durrett, and Junyi Jessy Li. 2019 · 2019
Later among the works it cites.
Complexity-weighted loss and diverse reranking for sentence simplification
Reno Kriz, João Sedoc, Marianna Apidianaki, Carolina Zheng, Gaurav Kumar, Eleni Miltsakaki, and Chris Callison-Burch. 2019 · 2019
Later among the works it cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Later among the works it cites.
Data-driven sentence simplification: Survey and benchmark
Fernando Alva-Manchego, Carolina Scarton, and Lucia Specia. 2020 · 2020
Closest in time.
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
Closest in time.
Learning to update natural language comments based on code changes
Sheena Panthaplackel, Pengyu Nie, Milos Gligoric, Junyi Jessy Li, and Raymond Mooney. 2020 · 2020
Closest in time.
ToTTo: A controlled table-to-text generation dataset
Ankur Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, and Dipanjan Das. 2020 · 2020
Closest in time.
Unsupervised commonsense question answering with self-talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2020 · 2020
Closest in time.
Discourse level factors for sentence deletion in text simplification
Yang Zhong, Chao Jiang, Wei Xu, and Junyi Jessy Li. 2020 · 2020
Closest in time.
Evaluating commonsense in pre-trained language models
Xuhui Zhou, Yue Zhang, Leyang Cui, and Dandan Huang. 2020 · 2020
Closest in time.
Decontextualization: Making sentences stand-alone
Eunsol Choi, Jennimaria Palomaki, Matthew Lamm, Tom Kwiatkowski, Dipanjan Das, and Michael Collins. 2021 · 2021
Closest in time.