# Trends, Limitations and Open Challenges in Automatic Readability Assessment Research

arXiv: https://arxiv.org/abs/2105.00973 · HTML: https://mlsanity.com/paper/2105.00973/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 105 references that are in the map.
- First posted on arXiv 3 May 2021.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Text Readability Assessment for Second Language Learners](https://mlsanity.com/paper/1906.07580/) (2019)
- [Supervised and Unsupervised Neural Approaches to Text Readability](https://mlsanity.com/paper/1907.11779/) (2019)
- [Linguistic Features for Readability Assessment](https://mlsanity.com/paper/2006.00377/) (2020)
- [Controlling Text Complexity in Neural Machine Translation](https://mlsanity.com/paper/1911.00835/) (2019)
- [ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis](https://mlsanity.com/paper/2103.04083/) (2021)
- [Language Modeling by Clustering with Word Embeddings for Text Readability Assessment](https://mlsanity.com/paper/1709.01888/) (2017)
- [Text as Environment: A Deep Reinforcement Learning Text Readability Assessment Model](https://mlsanity.com/paper/1912.05957/) (2019)
- [A Readable Read: Automatic Assessment of Language Learning Materials based on Linguistic Complexity](https://mlsanity.com/paper/1603.08868/) (2016)

## Built on by (most cited first, 28 of 28)

- [Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features](https://mlsanity.com/paper/2109.12258/) (2021)
- [Generating Summaries with Controllable Readability Levels](https://mlsanity.com/paper/2310.10623/) (2023)
- [BERT Embeddings for Automatic Readability Assessment](https://mlsanity.com/paper/2106.07935/) (2021)
- [ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment](https://mlsanity.com/paper/2305.14463/) (2023)
- [LFTK: Handcrafted Features in Computational Linguistics](https://mlsanity.com/paper/2305.15878/) (2023)
- [A Baseline Readability Model for Cebuano](https://mlsanity.com/paper/2203.17225/) (2022)
- [ReadCtrl: Personalizing text generation with readability-controlled instruction learning](https://mlsanity.com/paper/2406.09205/) (2024)
- [Measuring and Modifying the Readability of English Texts with GPT-4](https://mlsanity.com/paper/2410.14028/) (2024)
- [Prompt-based Learning for Text Readability Assessment](https://mlsanity.com/paper/2302.13139/) (2023)
- [A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment](https://mlsanity.com/paper/2502.13520/) (2025)
- [Automatic Readability Assessment of German Sentences with Transformer Ensembles](https://mlsanity.com/paper/2209.04299/) (2022)
- [An Open Multilingual System for Scoring Readability of Wikipedia](https://mlsanity.com/paper/2406.01835/) (2024)
- [LLMs in Education: Novel Perspectives, Challenges, and Opportunities](https://mlsanity.com/paper/2409.11917/) (2024)
- [Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://mlsanity.com/paper/2507.22753/) (2025)
- [Under the Microscope: Interpreting Readability Assessment Models for Filipino](https://mlsanity.com/paper/2110.00157/) (2021)
- [BasahaCorpus: An Expanded Linguistic Resource for Readability Assessment in Central Philippine Languages](https://mlsanity.com/paper/2310.11584/) (2023)
- [Strategies for Arabic Readability Modeling](https://mlsanity.com/paper/2407.03032/) (2024)
- [Easy-to-Read in Germany: A Survey on its Current State and Available Resources](https://mlsanity.com/paper/2306.03189/) (2023)
- [FPT: Feature Prompt Tuning for Few-shot Readability Assessment](https://mlsanity.com/paper/2404.02772/) (2024)
- [Eye Tracking Based Cognitive Evaluation of Automatic Readability Assessment Methods](https://mlsanity.com/paper/2502.11150/) (2025)
- [Optimizing Readability Using Genetic Algorithms](https://mlsanity.com/paper/2301.00374/) (2023)
- [Exploring Linguistic Features for Turkish Text Readability](https://mlsanity.com/paper/2306.03774/) (2023)
- [Cross-corpus Readability Compatibility Assessment for English Texts](https://mlsanity.com/paper/2306.09704/) (2023)
- [Readability Measures and Automatic Text Simplification: In the Search of a Construct](https://mlsanity.com/paper/2511.09536/) (2025)
- [Hierarchical Ranking Neural Network for Long Document Readability Assessment](https://mlsanity.com/paper/2511.21473/) (2025)
- [ComplexityMT: Benchmarking the Interaction Between Text Complexity and Machine Translation](https://mlsanity.com/paper/2606.05421/) (2026)
- [Flesch-Kincaid Readability Depends Only on the Topic Distribution in Long Texts under Topic Models](https://mlsanity.com/paper/2608.23327/) (2026)
- [Analyzing Traditional and Neural Approaches to Multilingual Readability Assessment](https://mlsanity.com/paper/2609.10792/) (2026)

## Abstract (arXiv)

Readability assessment is the task of evaluating the reading difficulty of a given piece of text. Although research on computational approaches to readability assessment is now two decades old, there is not much work on synthesizing this research. This article is a brief survey of contemporary research on developing computational models for readability assessment. We identify the common approaches, discuss their shortcomings, and identify some challenges for the future. Where possible, we also connect computational research with insights from related work in other disciplines such as education and psychology.