Multi-agent systems with internal quality signals and intelligent routing can outperform single-model approaches for text simplification tasks, even when adding lexical resources doesn't improve automatic metrics.
This paper presents three automatic systems for Spanish Easy-to-Read translation, submitted to a shared task. The best approach uses a multi-agent workflow combining two language models with quality signals and intelligent routing to simplify text while maintaining meaning. Results show this guided multi-agent approach outperforms simpler baseline methods.