R1-T1 is a novel framework that incorporates structured reasoning into machine translation, mimicking how human translators naturally employ multi-layered thought processes.

• Introduces reasoning-enhanced translation across diverse scenarios without task-specific fine-tuning
• Utilizes human-aligned CoT templates with adaptive reasoning patterns for different translation challenges
• Demonstrates superior performance across 11 languages and 40 translation directions
• Significantly improves translation quality in specialized domains (linguistic, medical, and legal)

This research transforms how language models approach translation tasks, providing a more adaptable and human-like framework that better preserves meaning across languages and specialized contexts.

R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning