---
source_url: https://arxiv.org/abs/2604.08947
ingested: 2026-05-08
sha256: 93ea97104ed9110c8ccef1599a67f1c3a748f8eb7d45d6953117894347d3a6a0
---

# MuTSE: A Human-in-the-Loop Multi-use Text Simplification Evaluator

**Authors:** Rares-Alexandru Roscan, Gabriel Petre, Adrian-Marius Dumitran et al.
**Published:** 2026-04-10
**Categories:** cs.CL, cs.AI
**arXiv:** https://arxiv.org/abs/2604.08947
**PDF:** https://arxiv.org/pdf/2604.08947

## Abstract

As Large Language Models (LLMs) become increasingly prevalent in text simplification, systematically evaluating their outputs across diverse prompting strategies and architectures remains a critical methodological challenge in both NLP research and Intelligent Tutoring Systems (ITS). Developing robu...