AI RESEARCH
LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance
arXiv CS.CL
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ArXi:2605.22567v1 Announce Type: new Reinforcement learning has proven effective for enhancing multi-step reasoning in large language models (LLMs), yet its benefits have not fully translated to multilingual contexts. Existing methods struggle with a fundamental trade-off: prioritizing input-language consistency severely hampers reasoning quality, while prioritizing reasoning often leads to unintended language drift toward English. We address this challenge with LANG, a novel framework that leverages language-conditioned hints to guide exploration in non-English reasoning tasks.