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We report two essential improvements in readability assessment: 1.
Roberta: A robustly optimized bert pretraining approach
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Linguistic complexity: Locality of syntactic dependencies
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Support vector machines
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Comprehending indirect replies: When and how are their conveyed meanings activated?
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Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
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CRC standard probability and statistics tables and formulae
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The acquisition of word meaning through global lexical co-occurrences
Ping Li, Curt Burgess, and Kevin Lund. 2000 · 2000
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Random forests
Leo Breiman. 2001 · 2001
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Characterizing semantic space: Neighborhood effects in word recognition
Lori Buchanan, Chris Westbury, and Curt Burgess. 2001 · 2001
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A statistical model for scientific readability
Luo Si and Jamie Callan. 2001 · 2001
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Nltk: The natural language toolkit
Edward Loper and Steven Bird. 2002 · 2002
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Latent dirichlet allocation
David M Blei, Andrew Y Ng, and Michael I Jordan. 2003 · 2003
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A language modeling approach to predicting reading difficulty
Kevyn Collins-Thompson and James P Callan. 2004 · 2004
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Reading level assessment using support vector machines and statistical language models
Sarah E. Schwarm and Mari Ostendorf. 2005 · 2005
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Cognitive linguistics
Vyvyan Evans. 2006 · 2006
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Combining lexical and grammatical features to improve readability measures for first and second language texts
Michael Heilman, Kevyn Collins-Thompson, Jamie Callan, and Maxine Eskenazi. 2007 · 2007
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Assessing text readability using cognitively based indices
Scott A Crossley, Jerry Greenfield, and Danielle S McNamara. 2008 · 2008
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Liblinear: A library for large linear classification
Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008 · 2008
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Lxper index: a curriculum-specific text readability assessment model for efl students in korea
Bruce W Lee and Jason Hyung-Jong Lee. 2020b · 2008
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There are many ways to be rich: Effects of three measures of semantic richness on visual word recognition
Penny M Pexman, Ian S Hargreaves, Paul D Siakaluk, Glen E Bodner, and Jamie Pope. 2008 · 2008
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Revisiting readability: A unified framework for predicting text quality
Emily Pitler and Ani Nenkova. 2008 · 2008
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Moving beyond kučera and francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for american english
Marc Brysbaert and Boris New. 2009 · 2009
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Cognitively motivated features for readability assessment
Lijun Feng, Noémie Elhadad, and Matt Huenerfauth. 2009 · 2009
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A machine learning approach to reading level assessment
S. E. Petersen and Mari Ostendorf. 2009 · 2009
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A multi-dimensional model for assessing the quality of answers in social Q&A sites
Zhemin Zhu, Delphine Bernhard, and Iryna Gurevych. 2009 · 2009
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Readability assessment for text simplification
Sandra Aluisio, Lucia Specia, Caroline Gasperin, and Carolina Scarton. 2010 · 2010
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A comparison of features for automatic readability assessment
Lijun Feng, Martin Jansche, Matt Huenerfauth, and Noémie Elhadad. 2010 · 2010
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A readability assessment of online parkinson’s disease information
Paul R Fitzsimmons, BD Michael, Joane L Hulley, and G Orville Scott. 2010 · 2010
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Online learning for latent dirichlet allocation
Matthew Hoffman, Francis R Bach, and David M Blei. 2010 · 2010
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Automatic analysis of syntactic complexity in second language writing
Xiaofei Lu. 2010 · 2010
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Mtld, vocd-d, and hd-d: A validation study of sophisticated approaches to lexical diversity assessment
Philip M McCarthy and Scott Jarvis. 2010 · 2010
Cited alongside, same era.
Coh-metrix: Capturing linguistic features of cohesion
Danielle S McNamara, Max M Louwerse, Philip M McCarthy, and Arthur C Graesser. 2010 · 2010
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Software Framework for Topic Modelling with Large Corpora
Radim Řehůřek and Petr Sojka. 2010 · 2010
Cited alongside, same era.
Sorting texts by readability
Kumiko Tanaka-Ishii, Satoshi Tezuka, and Hiroshi Terada. 2010 · 2010
Cited alongside, same era.
Libsvm: a library for support vector machines
Chih-Chung Chang and Chih-Jen Lin. 2011 · 2011
Cited alongside, same era.
Natural language processing (almost) from scratch
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011 · 2011
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Building e-rater® scoring models using machine learning methods
Jing Chen, James H Fife, Isaac I Bejar, and André A Rupp. 2016 · 2016
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Xgboost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin. 2016 · 2016
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Information-theoretical complexity metrics
John Hale. 2016 · 2016
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Towards semantic clarity in play therapy
Mary Anne Peabody and Charles E Schaefer. 2016 · 2016
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Readability-based sentence ranking for evaluating text simplification
Sowmya Vajjala and Detmar Meurers. 2016 · 2016
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Cited alongside, same era.
Using word segmentation and svm to assess readability of thai text for primary school students
Patcharanut Daowadung and Yaw-Huei Chen. 2011 · 2011
Cited alongside, same era.
Word maturity: A new metric for word knowledge
Thomas K Landauer, Kirill Kireyev, and Charles Panaccione. 2011 · 2011
Cited alongside, same era.
A corpus-based evaluation of syntactic complexity measures as indices of college-level esl writers’ language development
Xiaofei Lu. 2011 · 2011
Cited alongside, same era.
Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. 2011 · 2011
Cited alongside, same era.
Readaid: a robust and fully-automated readability assessment tool
Rani Qumsiyeh and Yiu-Kai Ng. 2011 · 2011
Cited alongside, same era.
Age-of-acquisition ratings for 30,000 english words
Victor Kuperman, Hans Stadthagen-Gonzalez, and Marc Brysbaert. 2012 · 2012
Cited alongside, same era.
Later among the works it cites.
Text readability assessment for second language learners
Menglin Xia, Ekaterina Kochmar, and Ted Briscoe. 2016 · 2016
Later among the works it cites.
Predicting short-and long-term vocabulary learning via semantic features of partial word knowledge
SungJin Nam, Gwen Frishkoff, and Kevyn Collins-Thompson. 2017 · 2017
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Towards the definition of linguistic metrics for evaluating text readability
Carla Pires, Afonso Cavaco, and Marina Vigário. 2017 · 2017
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Minimizing finite sums with the stochastic average gradient
Mark Schmidt, Nicolas Le Roux, and Francis Bach. 2017 · 2017
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Combining multiple corpora for readability assessment for people with cognitive disabilities
Victoria Yaneva, Constantin Orăsan, Richard Evans, and Omid Rohanian. 2017 · 2017
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Coherence-based automatic essay assessment
Diego Palma and John Atkinson. 2018 · 2018
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Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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A detailed evaluation of neural sequence-to-sequence models for in-domain and cross-domain text simplification
Sanja Štajner and Sergiu Nisioi. 2018 · 2018
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Onestopenglish corpus: A new corpus for automatic readability assessment and text simplification
Sowmya Vajjala and Ivana Lučić. 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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Automatic text difficulty estimation using embeddings and neural networks
Anna Filighera, Tim Steuer, and Christoph Rensing. 2019 · 2019
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A data-driven methodology to assess text complexity based on syntactic and semantic measurements
Diego Palma, Christian Soto, Mónica Veliz, Bernardo Riffo, and Antonio Gutiérrez. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 2019 · 2019
Later among the works it cites.
Cryptocurrency, confirmatory bias and news readability–evidence from the largest chinese cryptocurrency exchange
Shuyu Zhang, Xuanyu Zhou, Huifeng Pan, and Junyi Jia. 2019 · 2019
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Modeling lemma frequency bands for lexical complexity assessment of russian texts1
OV Blinova, Tarasov NA, Modina VV, and IS Blekanov. 2020 · 2020
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Linguistic features for readability assessment
Tovly Deutsch, Masoud Jasbi, and Stuart Shieber. 2020 · 2020
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spaCy: Industrial-strength Natural Language Processing in Python
Matthew Honnibal, Ines Montani, Sofie Van Landeghem, and Adriane Boyd. 2020 · 2020
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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
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Readnet: A hierarchical transformer framework for web article readability analysis
Changping Meng, Muhao Chen, Jie Mao, and Jennifer Neville. 2020 · 2020
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A machine learning approach to persian text readability assessment using a crowdsourced dataset
Hamid Mohammadi and Seyed Hossein Khasteh. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Fast and accurate neural CRF constituency parsing
Yu Zhang, Houquan Zhou, and Zhenghua Li. 2020 · 2020
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Machine learning for readability assessment and text simplification in crisis communication: A systematic review
Hieronymus Hansen, Adam Widera, Johannes Ponge, and Bernd Hellingrath. 2021 · 2021
Closest in time.
Supervised and Unsupervised Neural Approaches to Text Readability
Matej Martinc, Senja Pollak, and Marko Robnik-Šikonja. 2021 · 2021
Closest in time.
Trends, limitations and open challenges in automatic readability assessment research
Sowmya Vajjala. 2021 · 2021
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