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arXiv · 2602.22524

Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o

Samay Bhojwani·Swarnima Kain·Lisong Xu
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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.

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Samay Bhojwani, Swarnima Kain, Lisong Xu. 2026-02-26. Iterative Prompt Refinement for Dyslexia-Friendly Text Summarization Using GPT-4o. https://arxiv.org/abs/2602.22524

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