# Paper list (Text simplification)
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1. [A Survey of Automated Text Simplification](https://core.ac.uk/download/pdf/25778973.pdf)
2. [Sentence Simplification with Deep Reinforcement Learning](https://www.aclweb.org/anthology/D17-1062/)
3. [Integrating Transformer and Paraphrase Rules for Sentence Simplification](https://arxiv.org/abs/1810.11193)
4. [Optimizing Statistical Machine Translation for Text Simplification](https://www.aclweb.org/anthology/Q16-1029/)
5. [Attention Is All You Need](https://arxiv.org/abs/1706.03762)
6. [Controllable Sentence Simplification: Employing Syntactic and Lexical Constraints](https://arxiv.org/abs/1910.04387)
7. [Learning to Simplify Sentences with Quasi-Synchronous Grammar and Integer Programming](https://www.aclweb.org/anthology/D11-1038/)
8. [Lexi: A tool for adaptive, personalized text simplification](https://www.aclweb.org/anthology/C18-1021.pdf)
9. [Controllable Text Simplification with Lexical Constraint Loss](https://www.aclweb.org/anthology/P19-2036.pdf)
10. [QuickEdit: Editing Text & Translations by Crossing Words Out](https://www.aclweb.org/anthology/N18-1025/)
11. [Adversarial Example Generation with Syntactically Controlled Paraphrase Networks](https://arxiv.org/abs/1804.06059)
12. [Learning simplifications for specific target audiences](https://www.aclweb.org/anthology/P18-2113/) 2018.
13. [Benchmarking Lexical Simplification Systems](https://pdfs.semanticscholar.org/c811/2c63ab80cbdb23b5ad8a1d3a6d22a9112020.pdf) 2018.
14. [Simplifying Lexical Simplification: Do We Need Simplified Corpora?](https://pdfs.semanticscholar.org/26fb/d19be8e26b42f2d849c1db8a287012bfb188.pdf) 2015.
15. [Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation](https://arxiv.org/abs/1804.06609)
16. [BERT-based Lexical Substitution](https://www.aclweb.org/anthology/P19-1328/)
17. [A Simple BERT-Based Approach for Lexical Simplification](https://arxiv.org/abs/1907.06226)
18. [LEXenstein: A Framework for Lexical Simplification](https://pdfs.semanticscholar.org/e440/50369c49d2f70cf8645e550537b1eca46f3b.pdf)
19. [Anita: An Intelligent Text Adaptation Tool](https://www.aclweb.org/anthology/C16-2017.pdf)
20. [Lexical Simplification with Neural Ranking](https://www.aclweb.org/anthology/E17-2006.pdf)
21. [Exploring Neural Text Simplification Models](https://www.aclweb.org/anthology/P17-2014.pdf)
22. [Unsupervised Lexical Simplification for non-native speakers](https://dl.acm.org/citation.cfm?id=3016433)
23. [Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling](https://arxiv.org/pdf/1904.02817.pdf)
24. [TinyBERT: Distilling BERT for Natural Language Understanding](https://arxiv.org/abs/1909.10351)
25. [ELECTRA: PRE-TRAINING TEXT ENCODERS AS DISCRIMINATORS RATHER THAN GENERATORS](https://openreview.net/pdf?id=r1xMH1BtvB)
26. [A survey on lexical simplification](https://www.jair.org/index.php/jair/article/view/11091)
27. [SV000gg at SemEval-2016 Task 11: Heavy Gauge Complex Word Identification with System Voting](https://www.aclweb.org/anthology/S16-1149/)
28. [Retrofitting Word Vectors to Semantic Lexicons](https://arxiv.org/abs/1411.4166)
29. [A Mutual Information Maximization Perspective of Language Representation Learning](https://arxiv.org/abs/1910.08350)
30. [XLNet Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237)
31. [Heavy Gauge Complex Word Identification with System Voting](https://www.aclweb.org/anthology/S16-1149/)