# DysLexLens: A Low-Resource LLM Framework for Analysing Dyslexic Learners Insights from Online Forums

arXiv: https://arxiv.org/abs/2606.27619 · HTML: https://mlsanity.com/paper/2606.27619/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 27 references that are in the map.
- First posted on arXiv 26 Jun 2026.

## Builds on (most cited first, 2 of 2)

- [What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis](https://mlsanity.com/paper/2212.11311/) (2022)
- ["I've talked to ChatGPT about my issues last night.": Examining Mental Health Conversations with Large Language Models through Reddit Analysis](https://mlsanity.com/paper/2504.20320/) (2025)

## Abstract (arXiv)

Dyslexic learners increasingly use artificial intelligence (AI) tools to support reading, writing, organisation, and study-related tasks. However, their lived experiences with these tools remain largely underexamined. This paper proposes DysLexLens, a low-resource LLM framework, designed to analyse dyslexic learners experience with AI through online forum discussions. DysLexLens is designed as an end-to-end, evidence-traceable architecture which transforms noisy social media posts into a dictionary-driven corpora, provides knowledge-graph (KG)-based question reasoning, generates verifiable query responses, and enables response evaluation through quantitative and human-grounded assessment. DysLexLens has four key features. First, it employs a dictionary-driven filtering method to construct a more focused Reddit corpus on dyslexia and AI, filtering out noisy and weakly related posts to improve the relevance of data collected from low-resource forum contexts. Second, it integrates LLM-assisted semantic analysis with KG-based query reasoning to uncover meaningful patterns. Third, it has quantitative evaluation metrics (RAGAS and Query Robustness) to measure LLM-generated response performance. Fourth, it provides structured qualitative validation guidelines for assessing response quality, with a specific focus on hallucination and evidence alignment. We demonstrate the effectiveness of DysLexLens using dyslexia-related Reddit forum data and 30 questions. The results show its potential generalisability to other low-resource forum data contexts. DysLexLens, sample data, questions and evaluation results are available at Github to support reproducibility.