CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning (2026.acl-long)
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| Challenge: | Recent advances in large language models (LLMs) have produced strong performance in mathematical reasoning and code generation, but medical reasoning remains challenging because it requires domain knowledge. |
| Approach: | They propose a multilingual medical reasoning dataset with open-ended reasoning queries with a single verifiable answer that spans thirteen languages. |
| Outcome: | The proposed framework outperforms baselines and scales effectively across thirteen languages. |
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