Uniandes at TSAR 2025 Shared Task Multi-Agent CEFR Text Simplification with Automated Quality Assessment and Iterative Refinement

Felipe Arias Russi, Kevin Cohen Solano, Ruben Manrique


Abstract
We present an agent-based system for the TSAR 2025 Shared Task on Readability-Controlled Text Simplification, which requires simplifying English paragraphs from B2+ levels to target A2 or B1 levels while preserving meaning. Our approach employs specialized agents for keyword extraction, text generation, and evaluation, coordinated through an iterative refinement loop. The system integrates a CEFR vocabulary classifier, pretrained evaluation models, and few-shot learning from trial data. Through iterative feedback between the evaluator and writer agents, our system automatically refines outputs until they meet both readability and semantic preservation constraints. This architecture achieved 4th position among participating teams, showing the effectiveness of combining specialized LLMs with automated quality control strategies for text simplification.
Anthology ID:
2025.tsar-1.17
Volume:
Proceedings of the Fourth Workshop on Text Simplification, Accessibility and Readability (TSAR 2025)
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Matthew Shardlow, Fernando Alva-Manchego, Kai North, Regina Stodden, Horacio Saggion, Nouran Khallaf, Akio Hayakawa
Venues:
TSAR | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
211–216
Language:
URL:
https://preview.aclanthology.org/ingest-emnlp/2025.tsar-1.17/
DOI:
Bibkey:
Cite (ACL):
Felipe Arias Russi, Kevin Cohen Solano, and Ruben Manrique. 2025. Uniandes at TSAR 2025 Shared Task Multi-Agent CEFR Text Simplification with Automated Quality Assessment and Iterative Refinement. In Proceedings of the Fourth Workshop on Text Simplification, Accessibility and Readability (TSAR 2025), pages 211–216, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Uniandes at TSAR 2025 Shared Task Multi-Agent CEFR Text Simplification with Automated Quality Assessment and Iterative Refinement (Arias Russi et al., TSAR 2025)
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PDF:
https://preview.aclanthology.org/ingest-emnlp/2025.tsar-1.17.pdf