Neural Text Simplification
Neural Text Simplification is a computational approach to text simplification that employs neural network architectures to automatically transform complex textual inputs into simpler, more accessible versions while preserving meaning.
34
Publications
1.8K
Citations
95
Authors
43
Institutions
Publications per year
2017–2026
25
Parents
34
Exploring Neural Text Simplification Models
Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto et al. · 2017 · 199 citations · Full text
Learning a Lexical Simplifier Using Wikipedia
Colby Horn, Cathryn A. Manduca, David Kauchak · 2014 · 114 citations · Full text
Neural CRF Model for Sentence Alignment in Text Simplification
Chao Jiang, Mounica Maddela, Wuwei Lan et al. · 2020 · 103 citations · Full text
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43
University of Sheffield
Sheffield, United Kingdom
5 h-index
8 publications
605 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
8 publications
367 citations
University of Mannheim
Mannheim, Germany
3 h-index
4 publications
431 citations

Manchester Metropolitan University
Manchester, United Kingdom
2 h-index
3 publications
68 citations

University of Bucharest
Bucharest, Romania
2 h-index
3 publications
417 citations

Middlebury College
Middlebury (village), United States
2 h-index
4 publications
371 citations

Turing Institute
Glasgow, United Kingdom
1 h-index
1 publications
60 citations

University of Wolverhampton
Wolverhampton, United Kingdom
1 h-index
1 publications
40 citations
1–8 of 43
Repository · 4 publications · 81 citations
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Conference · 2 publications · 162 citations
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1 publications · 34 citations
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1 publications · 16 citations
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1 publications · 14 citations
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