Resources

Books and Surveys

• Data-Driven Sentence Simplification: Survey and Benchmark (Alva-Manchego et al., CL 2020)
• Automatic Text Simplification (Saggion, Synth. Lect. Hum. Lang 2017)
• A Survey on Lexical Simplification (Paetzold & Specia, JAIR 2017)
• A Survey of Automated Text Simplification (Shardlow, IJACSA 2014)
• A survey of Research on Text Simplification (Siddharthan, ITL 2014)

Tutorials

• Data-Driven Text Simplification (Štajner & Saggion, COLING 2018) [pdf] [slides] [bibliography]

Papers

• Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022) (Štajner et al., TSAR 2022)
• Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset (Shardlow et al., LRE 2022)
• Automatic Text Simplification for Social Good: Progress and Challenges (Stajner, Findings 2021)
• Controllable Text Simplification with Explicit Paraphrasing (Maddela et al., NAACL 2021)
• Controllable Sentence Simplification with a Unified Text-to-Text Transfer Transformer (Sheang & Saggion, INLG 2021)
• Automatic Text Simplification Tools for Deaf and Hard of Hearing Adults: Benefits of Lexical Simplification and Providing Users with Autonomy (Alonzo et al., CHI 2020)
• Controllable Sentence Simplification (Martin et al., LREC 2020)
• EASIER System. Language Resources for Cognitive Accessibility (Moreno et al., ASSETS 2020)
• Improving lexical coverage of text simplification systems for Spanish (Štajner et al., Expert Syst. Appl 2019)
• BLEU is Not Suitable for the Evaluation of Text Simplification (Sulem et al., EMNLP 2018)
• Semantic Structural Evaluation for Text Simplification (Sulem et al., NAACL 2018)
• Is this Sentence Difficult? Do you Agree? (Brunato et al., EMNLP 2018)
• Integrating Transformer and Paraphrase Rules for Sentence Simplification (Zhao et al., EMNLP 2018)
• Learning Simplifications for Specific Target Audiences (Scarton & Specia, ACL 2018)
• Exploring Neural Text Simplification Models (Nisioi et al., ACL 2017)
• Sentence Simplification with Deep Reinforcement Learning (Zhang & Lapata, EMNLP 2017)
• Unsupervised Lexical Simplification for Non-Native Speakers (Paetzold & Specia, AAAI 2016)
• Optimizing Statistical Machine Translation for Text Simplification (Xu et al., TACL 2016)
• YATS: Yet Another Text Simplifier (Ferrés et al., NLDB 2016)
• NLP–Based Readability Assessment of Health–Related Texts: a Case Study on Italian Informed Consent Forms (Venturi et al., Louhi 2015)
• Making It Simplext: Implementation and Evaluation of a Text Simplification System for Spanish (Saggion et al., ACM Trans. Access. Comput. 2015)
• Simplifying Lexical Simplification: Do We Need Simplified Corpora? (Glavaš & Štajner, ACL-IJCNLP 2015)
• A Deeper Exploration of the Standard PB-SMT Approach to Text Simplification and its Evaluation (Štajner et al., ACL-IJCNLP 2015)
• FLELex: a graded lexical resource for French foreign learners (François et al., LREC 2014)
• Hybrid text simplification using synchronous dependency grammars with hand-written and automatically harvested rules (Siddharthan & Mandya, EACL 2014)
• Simplify or Help?: Text Simplification Strategies for People with Dyslexia (Rello et al., W4A 2013).
• OECD Skills Outlook 2013: First Results from the Survey of Adult Skills (OECD, 2013)
• Can Spanish Be Simpler? LexSiS: Lexical Simplification for Spanish (Bott et al., COLING 2012)
• Putting it Simply: a Context-Aware Approach to Lexical Simplification (Biran et al., ACL 2011)
• Text Simplification in Simplext. Making Text More Accessible (Saggion et al., Proces. del Leng. Natural 2011)
• Simple English Wikipedia: A New Text Simplification Task (Coster & Kauchak, ACL 2011)
• Towards Brazilian Portuguese Automatic Text Simplification Systems (Aluísio et al., DocEng 2008)