AI RESEARCH
Right at My Level: A Unified Multilingual Framework for Proficiency-Aware Text Simplification
arXiv CS.CL
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ArXi:2604.05302v1 Announce Type: new Text simplification s second language (L2) learning by providing comprehensible input, consistent with the Input Hypothesis. However, constructing personalized parallel corpora is costly, while existing large language model (LLM)-based readability control methods rely on pre-labeled sentence corpora and primarily target English. We propose Re-RIGHT, a unified reinforcement learning framework for adaptive multilingual text simplification without parallel corpus supervision.