# RALS: Resources and Baselines for Romanian Automatic Lexical Simplification

arXiv: https://arxiv.org/abs/2607.20078 · HTML: https://mlsanity.com/paper/2607.20078/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 60 references that are in the map.
- First posted on arXiv 22 Jul 2026.

## Builds on (most cited first, 16 of 16)

- [FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language](https://mlsanity.com/paper/2506.20920/) (2025)
- [The birth of Romanian BERT](https://mlsanity.com/paper/2009.08712/) (2020)
- [A Report on the Complex Word Identification Shared Task 2018](https://mlsanity.com/paper/1804.09132/) (2018)
- [On the Ethical Considerations of Text Simplification](https://mlsanity.com/paper/2204.09565/) (2022)
- [Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification](https://mlsanity.com/paper/2302.02888/) (2023)
- [SemEval-2021 Task 1: Lexical Complexity Prediction](https://mlsanity.com/paper/2106.00473/) (2021)
- [Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset](https://mlsanity.com/paper/2102.08773/) (2021)
- [UniHD at TSAR-2022 Shared Task: Is Compute All We Need for Lexical Simplification?](https://mlsanity.com/paper/2301.01764/) (2023)
- [One Size Does Not Fit All: The Case for Personalised Word Complexity Models](https://mlsanity.com/paper/2205.02564/) (2022)
- [Luck, skill, and depth of competition in games and social hierarchies](https://mlsanity.com/paper/2312.04711/) (2023)
- [On the Similarities Between Native, Non-native and Translated Texts](https://mlsanity.com/paper/1609.03204/) (2016)
- [Japanese Lexical Complexity for Non-Native Readers: A New Dataset](https://mlsanity.com/paper/2306.17399/) (2023)
- [Deep Learning Approaches to Lexical Simplification: A Survey](https://mlsanity.com/paper/2305.12000/) (2023)
- [RoDia: A New Dataset for Romanian Dialect Identification from Speech](https://mlsanity.com/paper/2309.03378/) (2023)
- [ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification](https://mlsanity.com/paper/2209.09034/) (2022)
- [Multilingual Controllable Transformer-Based Lexical Simplification](https://mlsanity.com/paper/2307.02120/) (2023)

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

- [LLM-as-a-Judge for Low-Resource Languages: Adapting Ragas and Comparative Ranking for Romanian](https://mlsanity.com/paper/2610.00406/) (2026)

## Abstract (arXiv)

We introduce the first dataset that jointly covers both lexical complexity prediction (LCP) annotations and lexical simplification (LS) for Romanian, along with a comparison of lexical simplification approaches. We propose a methodology for ordering simplification suggestions using a pairwise ranking approximation method, arranging candidates from simple to complex based on a separate set of human judgments. In addition, we provide human lexical complexity annotations for 3,921 word samples in context. Finally, we explore several novel pipelines for complexity prediction and simplification and present the first text simplification system for Romanian.