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Text simplification is a common task where the text is adapted to make it easier to understand.
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, et al. 2020 · 1901
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
Earlier work this paper cites.
Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2019 · 1912
Earlier work this paper cites.
A new readability yardstick
Rudolph Flesch. 1948 · 1948
Earlier work this paper cites.
The concept of readability
Edgar Dale and Jeanne S Chall. 1949 · 1949
Earlier work this paper cites.
Technique of clear writing
Robert Gunning et al. 1952 · 1952
Earlier work this paper cites.
A new readability formula for primary-grade reading materials
George Spache. 1953 · 1953
Earlier work this paper cites.
Automated readability index
RJ Senter and Edgar A Smith. 1967 · 1967
Earlier work this paper cites.
Phrase and paraphrase: Some innovative uses of language
Lila R Gleitman and Henry Gleitman. 1970 · 1970
Earlier work this paper cites.
Assessing readability
George R Klare. 1974 · 1974
Earlier work this paper cites.
A computer readability formula designed for machine scoring
Meri Coleman and Ta Lin Liau. 1975 · 1975
Earlier work this paper cites.
Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel
J Peter Kincaid, Robert P Fishburne Jr, Richard L Rogers, and Brad S Chissom. 1975 · 1975
Earlier work this paper cites.
Simplification or elaboration? the effects of two types of text modifications on foreign language reading comprehension
Steven Ross, Michael H Long, and Yasukata Yano. 1991 · 1991
Earlier work this paper cites.
The literacy dictionary: The vocabulary of reading and writing
Theodore L Harris and Richard E Hodges. 1995 · 1995
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
Earlier work this paper cites.
Minimum error rate training in statistical machine translation
Franz Josef Och. 2003 · 2003
Earlier work this paper cites.
Smart Language: Readers, Readability, and the Grading of Text
William H DuBay. 2007 · 2007
Earlier work this paper cites.
A survey on text simplification
Punardeep Sikka and Vijay Mago. 2020 · 2008
Earlier work this paper cites.
Text simplification for children
Jan De Belder and Marie-Francine Moens. 2010 · 2010
Earlier work this paper cites.
Collecting highly parallel data for paraphrase evaluation
David Chen and William B Dolan. 2011 · 2011
Earlier work this paper cites.
A distributional approach to controlled text generation
Muhammad Khalifa, Hady Elsahar, and Marc Dymetman. 2020 · 2012
Earlier work this paper cites.
What is a paraphrase?
Rahul Bhagat and Eduard Hovy. 2013 · 2013
Cited alongside, same era.
Frequent words improve readability and short words improve understandability for people with dyslexia
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Cited alongside, same era.
An evaluation of syntactic simplification rules for people with autism
Richard Evans, Constantin Orasan, and Iustin Dornescu. 2014 · 2014
Cited alongside, same era.
A survey of research on text simplification
Advaith Siddharthan. 2014 · 2014
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.
Controlling output length in neural encoder-decoders
Yuta Kikuchi, Graham Neubig, Ryohei Sasano, Hiroya Takamura, and Manabu Okumura. 2016 · 2016
Towards document-level paraphrase generation with sentence rewriting and reordering
Zhe Lin, Yitao Cai, and Xiaojun Wan. 2021 · 2021
Later among the works it cites.
Dexperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A Smith, and Yejin Choi. 2021 · 2021
Later among the works it cites.
A survey of approaches to automatic question generation: from 2019 to early 2021
Chao-Yi Lu and Sin-En Lu. 2021 · 2021
Later among the works it cites.
Automatic speech recognition: a survey
Mishaim Malik, Muhammad Kamran Malik, Khawar Mehmood, and Imran Makhdoom. 2021 · 2021
Later among the works it cites.
Investigating pretrained language models for graph-to-text generation
Leonardo FR Ribeiro, Martin Schmitt, Hinrich Schütze, and Iryna Gurevych. 2021 · 2021
Later among the works it cites.
Multitask prompted training enables zero-shot task generalization
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Cited alongside, same era.
Controlling politeness in neural machine translation via side constraints
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Cited alongside, same era.
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Later among the works it cites.
Document-level text simplification: Dataset, criteria and baseline
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Later among the works it cites.
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Fine-grained controllable text generation using non-residual prompting
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Palm: Scaling language modeling with pathways
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