# Redefining Simplicity: Benchmarking Large Language Models from Lexical to Document Simplification

arXiv: https://arxiv.org/abs/2502.08281 · HTML: https://mlsanity.com/paper/2502.08281/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Feb 2025.

## Built on by (most cited first, 6 of 6)

- [Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://mlsanity.com/paper/2507.22753/) (2025)
- [APIO: Automatic Prompt Induction and Optimization for Grammatical Error Correction and Text Simplification](https://mlsanity.com/paper/2508.09378/) (2025)
- [Towards Trustworthy Lexical Simplification: Exploring Safety and Efficiency with Small LLMs](https://mlsanity.com/paper/2509.25086/) (2025)
- [Profiling German Text Simplification with Interpretable Model-Fingerprints](https://mlsanity.com/paper/2601.13050/) (2026)
- [A Human-in-the-Loop Corpus for LLM-Based Simplification of Scientific Summaries](https://mlsanity.com/paper/2607.25630/) (2026)
- [An Exploratory Evaluation of LLM-Assisted Rewriting of Moderate-Complexity Financial Sentences for DisCoCat-Based Sentiment Analysis](https://mlsanity.com/paper/2608.07439/) (2026)

## Abstract (arXiv)

Text simplification (TS) refers to the process of reducing the complexity of a text while retaining its original meaning and key information. Existing work only shows that large language models (LLMs) have outperformed supervised non-LLM-based methods on sentence simplification. This study offers the first comprehensive analysis of LLM performance across four TS tasks: lexical, syntactic, sentence, and document simplification. We compare lightweight, closed-source and open-source LLMs against traditional non-LLM methods using automatic metrics and human evaluations. Our experiments reveal that LLMs not only outperform non-LLM approaches in all four tasks but also often generate outputs that exceed the quality of existing human-annotated references. Finally, we present some future directions of TS in the era of LLMs.