# Text Adaptation to Plain Language and Easy Read via Automatic Post-Editing Cycles

arXiv: https://arxiv.org/abs/2509.11991 · HTML: https://mlsanity.com/paper/2509.11991/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 48 references that are in the map.
- First posted on arXiv 15 Sep 2025.

## Builds on (most cited first, 23 of 23)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [The Llama 3 Herd of Models](https://mlsanity.com/paper/2407.21783/) (2024)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [QLoRA: Efficient Finetuning of Quantized LLMs](https://mlsanity.com/paper/2305.14314/) (2023)
- [Controllable Sentence Simplification](https://mlsanity.com/paper/1910.02677/) (2019)
- [Keep it Simple: Unsupervised Simplification of Multi-Paragraph Text](https://mlsanity.com/paper/2107.03444/) (2021)
- [BLESS: Benchmarking Large Language Models on Sentence Simplification](https://mlsanity.com/paper/2310.15773/) (2023)
- [Split and Rephrase](https://mlsanity.com/paper/1707.06971/) (2017)
- [Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification](https://mlsanity.com/paper/2302.02888/) (2023)
- [Transforming Complex Sentences into a Semantic Hierarchy](https://mlsanity.com/paper/1906.01038/) (2019)
- [Sentence Simplification via Large Language Models](https://mlsanity.com/paper/2302.11957/) (2023)
- [Controlling Pre-trained Language Models for Grade-Specific Text Simplification](https://mlsanity.com/paper/2305.14993/) (2023)
- [Simplicity Level Estimate (SLE): A Learned Reference-Less Metric for Sentence Simplification](https://mlsanity.com/paper/2310.08170/) (2023)
- [Exploring Large Language Models to generate Easy to Read content](https://mlsanity.com/paper/2407.20046/) (2024)
- [Split and Rephrase with Large Language Models](https://mlsanity.com/paper/2312.11075/) (2023)
- [Evaluating Document Simplification: On the Importance of Separately Assessing Simplicity and Meaning Preservation](https://mlsanity.com/paper/2404.03278/) (2024)
- [LLM-based Text Simplification and its Effect on User Comprehension and Cognitive Load](https://mlsanity.com/paper/2505.01980/) (2025)
- [Automating Easy Read Text Segmentation](https://mlsanity.com/paper/2406.11464/) (2024)
- [Multilingual Controllable Transformer-Based Lexical Simplification](https://mlsanity.com/paper/2307.02120/) (2023)
- [A User-Centered Evaluation of Spanish Text Simplification](https://mlsanity.com/paper/2308.07556/) (2023)
- [Language Resources in Spanish for Automatic Text Simplification across Domains](https://mlsanity.com/paper/2409.20466/) (2024)

## Abstract (arXiv)

We describe Vicomtech's participation in the CLEARS challenge on text adaptation to Plain Language and Easy Read in Spanish. Our approach features automatic post-editing of different types of initial Large Language Model adaptations, where successive adaptations are generated iteratively until readability and similarity metrics indicate that no further adaptation refinement can be successfully performed. Taking the average of all official metrics, our submissions achieved first and second place in Plain language and Easy Read adaptation, respectively.