mlsanityData to 7 Oct 2026

On the Ethical Considerations of Text Simplification

arXiv 2204.09565 ↗First posted 20 Apr 2022cs.CL cs.ET cs.HCcited by 20

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Abstract (arXiv)

This paper outlines the ethical implications of text simplification within the framework of assistive systems. We argue that a distinction should be made between the technologies that perform text simplification and the realisation of these in assistive technologies. When using the latter as a motivation for research, it is important that the subsequent ethical implications be carefully considered. We provide guidelines for the framing of text simplification independently of assistive systems, as well as suggesting directions for future research and discussion based on the concerns raised.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 12 of its 60 references that are in the map. First posted on arXiv 20 Apr 2022.

Builds on

12 of 60 references.

References · 12

  1. 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 691
  2. 2017Challenges in Data-to-Document Generationcited by 226
  3. 2017Faithful to the Original: Fact Aware Neural Abstractive Summarizationcited by 141
  4. 2017Sentence Simplification with Deep Reinforcement Learningcited by 107
  5. 2019EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editingcited by 63
  6. 2020Controllable Text Simplification with Explicit Paraphrasingcited by 53
  7. 2021Text Simplification by Taggingcited by 27
  8. 2021Document-Level Text Simplification: Dataset, Criteria and Baselinecited by 27
  9. 2020A Survey on Text Simplificationcited by 13
  10. 2018Assessing Language Proficiency from Eye Movements in Readingcited by 12
  11. 2020Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplificationcited by 12
  12. 2021Predicting Text Readability from Scrolling Interactionscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 9; 2024: 2; 2025: 4; 2026: 2.

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  1. 2023The Intended Uses of Automated Fact-Checking Artefacts: Why, How and Whocited by 19
  2. 2023Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSAcited by 15
  3. 2023DEPLAIN: A German Parallel Corpus with Intralingual Translations into Plain Language for Sentence and Document Simplificationcited by 14
  4. 2023Simplicity Level Estimate (SLE): A Learned Reference-Less Metric for Sentence Simplificationcited by 14
  5. 2024InfoLossQA: Characterizing and Recovering Information Loss in Text Simplificationcited by 14
  6. 2022One Size Does Not Fit All: The Case for Personalised Word Complexity Modelscited by 10
  7. 2025Progressive Document-level Text Simplification via Large Language Modelscited by 5
  8. 2023Automatic and Human-AI Interactive Text Generationcited by 4
  9. 2022Analyzing Multi-Task Learning for Abstractive Text Summarizationcited by 3
  10. 2023Lexical Complexity Prediction: An Overviewcited by 3
  11. 2023SimpLex: a lexical text simplification architecturecited by 3
  12. 2023Context-Aware Document Simplificationcited by 3
8 more
  1. 2024Digital Comprehensibility Assessment of Simplified Texts among Persons with Intellectual Disabilitiescited by 3
  2. 2022Cognitive Simplification Operations Improve Text Simplificationcited by 2
  3. 2025Facilitating Cognitive Accessibility with LLMs: A Multi-Task Approach to Easy-to-Read Text Generationcited by 2
  4. 2023A User-Centered Evaluation of Spanish Text Simplificationcited by 1
  5. 2026RALS: Resources and Baselines for Romanian Automatic Lexical Simplificationcited by 1
  6. 2025A Hybrid Multi-Agent Prompting Approach for Simplifying Complex Sentencescited by 0
  7. 2025THM@SimpleText 2025 -- Task 1.1: Revisiting Text Simplification based on Complex Terms for Non-Expertscited by 0
  8. 2026No Reader Left Behind: Multi-Agent Summaries Everyone Can Understandcited by 0