Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o
#dyslexia #text summarization #GPT-4o #prompt refinement #accessibility #readability #artificial intelligence #assistive technology
📌 Key Takeaways
- Dyslexia affects 10% of global population, creating reading fluency challenges
- Researchers developed an iterative prompt refinement pipeline using GPT-4o
- Pipeline successfully met readability targets for most summaries within four attempts
- Study establishes empirical baseline for accessibility-driven NLP summarization
📖 Full Retelling
Researchers Samay Bhojwani, Swarnima Kain, and Lisong Xu published a study on arXiv on February 26, 2026, detailing their development of an iterative prompt-based refinement pipeline using GPT-4o to create dyslexia-friendly text summaries, addressing the linguistic complexity barriers faced by approximately 10% of the global population with dyslexia. The research represents a significant advancement in assistive technologies by focusing on linguistic accessibility rather than just visual presentation, which has been the primary approach of existing solutions. The study evaluated the pipeline on approximately 2,000 news article samples, applying a readability target of Flesch Reading Ease >= 90, which is considered very easy to read. Results demonstrated that the majority of summaries successfully met the readability threshold within four attempts, with many achieving this on the first try. A composite score combining readability and semantic fidelity showed consistent performance across the dataset, ranging from 0.13 to 0.73 with a typical value near 0.55, establishing an empirical baseline for accessibility-driven natural language processing summarization.
🏷️ Themes
Accessibility, Artificial Intelligence, Assistive Technology
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Original Source
--> Computer Science > Computation and Language arXiv:2602.22524 [Submitted on 26 Feb 2026] Title: Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o Authors: Samay Bhojwani , Swarnima Kain , Lisong Xu View a PDF of the paper titled Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o, by Samay Bhojwani and 2 other authors View PDF Abstract: Dyslexia affects approximately 10% of the global population and presents persistent challenges in reading fluency and text comprehension. While existing assistive technologies address visual presentation, linguistic complexity remains a substantial barrier to equitable access. This paper presents an empirical study on dyslexia-friendly text summarization using an iterative prompt-based refinement pipeline built on GPT-4o. We evaluate the pipeline on approximately 2,000 news article samples, applying a readability target of Flesch Reading Ease >= 90. Results show that the majority of summaries meet the readability threshold within four attempts, with many succeeding on the first try. A composite score combining readability and semantic fidelity shows stable performance across the dataset, ranging from 0.13 to 0.73 with a typical value near 0.55. These findings establish an empirical baseline for accessibility-driven NLP summarization and motivate further human-centered evaluation with dyslexic readers. Subjects: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI) Cite as: arXiv:2602.22524 [cs.CL] (or arXiv:2602.22524v1 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2602.22524 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Lisong Xu [ view email ] [v1] Thu, 26 Feb 2026 01:46:40 UTC (600 KB) Full-text links: Access Paper: View a PDF of the paper titled Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o, by Samay Bhojwani and 2 other authors View PDF view license Curre...
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