mlsanityData to 14 Oct 2026

Traditional Readability Formulas Compared for English

arXiv 2301.02975 ↗First posted 8 Jan 2023cs.CL cs.LGcited by 4

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Abstract (arXiv)

Traditional English readability formulas, or equations, were largely developed in the 20th century. Nonetheless, many researchers still rely on them for various NLP applications. This phenomenon is presumably due to the convenience and straightforwardness of readability formulas. In this work, we contribute to the NLP community by 1. introducing New English Readability Formula (NERF), 2. recalibrating the coefficients of old readability formulas (Flesch-Kincaid Grade Level, Fog Index, SMOG Index, Coleman-Liau Index, and Automated Readability Index), 3. evaluating the readability formulas, for use in text simplification studies and medical texts, and 4. developing a Python-based program for the wide application to various NLP projects.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 10 of its 69 references that are in the map. First posted on arXiv 8 Jan 2023.

Builds on

10 of 69 references.

References · 10

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,811
  3. 2018Deep contextualized word representationscited by 2,290
  4. 2020ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformationscited by 101
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  7. 2021Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Featurescited by 36
  8. 2021ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysiscited by 16
  9. 2020LXPER Index 2.0: Improving Text Readability Assessment Model for L2 English Students in Koreacited by 4
  10. 2020LXPER Index: a curriculum-specific text readability assessment model for EFL students in Koreacited by 2

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Cited by year

Citing papers per year: 2023: 3; 2024: 1.

4 papers.

  1. 2023LFTK: Handcrafted Features in Computational Linguisticscited by 19
  2. 2023Prompt-based Learning for Text Readability Assessmentcited by 8
  3. 2024Do LLMs Implicitly Determine the Suitable Text Difficulty for Users?cited by 4
  4. 2023Exploring Linguistic Features for Turkish Text Readabilitycited by 0