mlsanityData to 7 Oct 2026

A Word-Complexity Lexicon and A Neural Readability Ranking Model for Lexical Simplification

arXiv 1810.05754 ↗First posted 12 Oct 2018cs.CLcited by 24

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Abstract (arXiv)

Current lexical simplification approaches rely heavily on heuristics and corpus level features that do not always align with human judgment. We create a human-rated word-complexity lexicon of 15,000 English words and propose a novel neural readability ranking model with a Gaussian-based feature vectorization layer that utilizes these human ratings to measure the complexity of any given word or phrase. Our model performs better than the state-of-the-art systems for different lexical simplification tasks and evaluation datasets. Additionally, we also produce SimplePPDB++, a lexical resource of over 10 million simplifying paraphrase rules, by applying our model to the Paraphrase Database (PPDB).

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Oct 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 6; 2023: 6; 2024: 4; 2025: 2; 2026: 1.

24 papers.

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  1. 2021SemEval-2021 Task 1: Lexical Complexity Predictioncited by 19
  2. 2021Predicting Lexical Complexity in English Texts: The Complex 2.0 Datasetcited by 15
  3. 2022One Size Does Not Fit All: The Case for Personalised Word Complexity Modelscited by 10
  4. 2023Teaching the Pre-trained Model to Generate Simple Texts for Text Simplificationcited by 10
  5. 2024The SAMER Arabic Text Simplification Corpuscited by 9
  6. 2022A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced Losscited by 7
  7. 2021Automated Speech Scoring System Under The Lens: Evaluating and interpreting the linguistic cues for language proficiencycited by 6
  8. 2025Opportunities and Challenges of LLMs in Education: An NLP Perspectivecited by 6
  9. 2023Exploiting Summarization Data to Help Text Simplificationcited by 5
  10. 2023Deep Learning Approaches to Lexical Simplification: A Surveycited by 4
  11. 2023Meta-Tuning LLMs to Leverage Lexical Knowledge for Generalizable Language Style Understandingcited by 4
  12. 2021LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Predictioncited by 3
12 more
  1. 2021Learning Syntactic Dense Embedding with Correlation Graph for Automatic Readability Assessmentcited by 3
  2. 2022Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identificationcited by 3
  3. 2022Unsupervised Simplification of Legal Textscited by 3
  4. 2023Lexical Complexity Prediction: An Overviewcited by 3
  5. 2023SimpLex: a lexical text simplification architecturecited by 3
  6. 2022SimpleBERT: A Pre-trained Model That Learns to Generate Simple Wordscited by 1
  7. 2022Tapping the Potential of Coherence and Syntactic Features in Neural Models for Automatic Essay Scoringcited by 1
  8. 2024Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identificationcited by 1
  9. 2024Readability-guided Idiom-aware Sentence Simplification (RISS) for Chinesecited by 1
  10. 2024Understanding the Cognitive Complexity in Language Elicited by Product Imagescited by 0
  11. 2025Readability Measures and Automatic Text Simplification: In the Search of a Constructcited by 0
  12. 2026ComplexityMT: Benchmarking the Interaction Between Text Complexity and Machine Translationcited by 0