Learning When to Translate for Multilingual Reasoning

ArXi:2606.02465v1 Announce Type: cross Reasoning language models (RLMs) achieve strong performance on complex reasoning tasks, but still exhibit substantial multilingual reasoning gaps, largely due to language-understanding failures in non-English inputs. English translation can mitigate these failures by expressing non-English inputs in a form that RLMs can reliably interpret, yet translating every input is unnecessary when the model can reason reliably from the original query.