# A User-Centered Evaluation of Spanish Text Simplification

arXiv: https://arxiv.org/abs/2308.07556 · HTML: https://mlsanity.com/paper/2308.07556/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 61 references that are in the map.
- First posted on arXiv 15 Aug 2023.

## Builds on (most cited first, 17 of 17)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [A Primer in BERTology: What we know about how BERT works](https://mlsanity.com/paper/2002.12327/) (2020)
- [XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization](https://mlsanity.com/paper/2003.11080/) (2020)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [Spanish Pre-trained BERT Model and Evaluation Data](https://mlsanity.com/paper/2308.02976/) (2023)
- [Supervised and Unsupervised Neural Approaches to Text Readability](https://mlsanity.com/paper/1907.11779/) (2019)
- [Evaluating Factuality in Text Simplification](https://mlsanity.com/paper/2204.07562/) (2022)
- [Semantic Structural Evaluation for Text Simplification](https://mlsanity.com/paper/1810.05022/) (2018)
- [Unsupervised Neural Text Simplification](https://mlsanity.com/paper/1810.07931/) (2018)
- [On the Ethical Considerations of Text Simplification](https://mlsanity.com/paper/2204.09565/) (2022)
- [Dialect-robust Evaluation of Generated Text](https://mlsanity.com/paper/2211.00922/) (2022)
- [Strong Baselines for Complex Word Identification across Multiple Languages](https://mlsanity.com/paper/1904.05953/) (2019)
- [ALBETO and DistilBETO: Lightweight Spanish Language Models](https://mlsanity.com/paper/2204.09145/) (2022)

## Built on by (most cited first, 1 of 1)

- [Text Adaptation to Plain Language and Easy Read via Automatic Post-Editing Cycles](https://mlsanity.com/paper/2509.11991/) (2025)

## Abstract (arXiv)

We present an evaluation of text simplification (TS) in Spanish for a production system, by means of two corpora focused in both complex-sentence and complex-word identification. We compare the most prevalent Spanish-specific readability scores with neural networks, and show that the latter are consistently better at predicting user preferences regarding TS. As part of our analysis, we find that multilingual models underperform against equivalent Spanish-only models on the same task, yet all models focus too often on spurious statistical features, such as sentence length. We release the corpora in our evaluation to the broader community with the hopes of pushing forward the state-of-the-art in Spanish natural language processing.