# Findings of the TSAR-2022 Shared Task on Multilingual Lexical Simplification

arXiv: https://arxiv.org/abs/2302.02888 · HTML: https://mlsanity.com/paper/2302.02888/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 60 references that are in the map.
- First posted on arXiv 6 Feb 2023.

## Builds on (most cited first, 13 of 13)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://mlsanity.com/paper/1912.08777/) (2019)
- [A Report on the Complex Word Identification Shared Task 2018](https://mlsanity.com/paper/1804.09132/) (2018)
- [VisualSem: A High-quality Knowledge Graph for Vision and Language](https://mlsanity.com/paper/2008.09150/) (2020)
- [SemEval-2021 Task 1: Lexical Complexity Prediction](https://mlsanity.com/paper/2106.00473/) (2021)
- [Lexical Simplification Benchmarks for English, Portuguese, and Spanish](https://mlsanity.com/paper/2209.05301/) (2022)
- [UniHD at TSAR-2022 Shared Task: Is Compute All We Need for Lexical Simplification?](https://mlsanity.com/paper/2301.01764/) (2023)
- [LSBert: A Simple Framework for Lexical Simplification](https://mlsanity.com/paper/2006.14939/) (2020)
- [Chinese Lexical Simplification](https://mlsanity.com/paper/2010.07048/) (2020)
- [MANTIS at TSAR-2022 Shared Task: Improved Unsupervised Lexical Simplification with Pretrained Encoders](https://mlsanity.com/paper/2212.09855/) (2022)
- [ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification](https://mlsanity.com/paper/2209.09034/) (2022)

## Built on by (most cited first, 20 of 20)

- [BLESS: Benchmarking Large Language Models on Sentence Simplification](https://mlsanity.com/paper/2310.15773/) (2023)
- [On the application of Large Language Models for language teaching and assessment technology](https://mlsanity.com/paper/2307.08393/) (2023)
- [mEdIT: Multilingual Text Editing via Instruction Tuning](https://mlsanity.com/paper/2402.16472/) (2024)
- [LLMs in Education: Novel Perspectives, Challenges, and Opportunities](https://mlsanity.com/paper/2409.11917/) (2024)
- [Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://mlsanity.com/paper/2507.22753/) (2025)
- [Deep Learning Approaches to Lexical Simplification: A Survey](https://mlsanity.com/paper/2305.12000/) (2023)
- [Automatic and Human-AI Interactive Text Generation](https://mlsanity.com/paper/2310.03878/) (2023)
- [On the Automatic Generation and Simplification of Children's Stories](https://mlsanity.com/paper/2310.18502/) (2023)
- [Spivavtor: An Instruction Tuned Ukrainian Text Editing Model](https://mlsanity.com/paper/2404.18880/) (2024)
- [Multilingual Controllable Transformer-Based Lexical Simplification](https://mlsanity.com/paper/2307.02120/) (2023)
- [Towards Trustworthy Lexical Simplification: Exploring Safety and Efficiency with Small LLMs](https://mlsanity.com/paper/2509.25086/) (2025)
- [Multilingual Lexical Simplification via Paraphrase Generation](https://mlsanity.com/paper/2307.15286/) (2023)
- [Lexical Complexity Prediction and Lexical Simplification for Catalan and Spanish: Resource Creation, Quality Assessment, and Ethical Considerations](https://mlsanity.com/paper/2404.07814/) (2024)
- [RALS: Resources and Baselines for Romanian Automatic Lexical Simplification](https://mlsanity.com/paper/2607.20078/) (2026)
- [mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models](https://mlsanity.com/paper/2305.13684/) (2023)
- [Unsupervised Lexical Simplification with Context Augmentation](https://mlsanity.com/paper/2311.00310/) (2023)
- [Society of Medical Simplifiers](https://mlsanity.com/paper/2410.09631/) (2024)
- [Text Adaptation to Plain Language and Easy Read via Automatic Post-Editing Cycles](https://mlsanity.com/paper/2509.11991/) (2025)
- [OasisSimp: An Open-source Asian-English Sentence Simplification Dataset](https://mlsanity.com/paper/2603.14111/) (2026)
- [HULAT2 at MER-TRANS 2026: Governed Multi-Agent Simplification for Spanish Easy-to-Read Generation](https://mlsanity.com/paper/2607.02381/) (2026)

## Abstract (arXiv)

We report findings of the TSAR-2022 shared task on multilingual lexical simplification, organized as part of the Workshop on Text Simplification, Accessibility, and Readability TSAR-2022 held in conjunction with EMNLP 2022. The task called the Natural Language Processing research community to contribute with methods to advance the state of the art in multilingual lexical simplification for English, Portuguese, and Spanish. A total of 14 teams submitted the results of their lexical simplification systems for the provided test data. Results of the shared task indicate new benchmarks in Lexical Simplification with English lexical simplification quantitative results noticeably higher than those obtained for Spanish and (Brazilian) Portuguese.