mlsanityData to 7 Oct 2026

HiMed: Incentivizing Hindi Reasoning in Medical LLMs

arXiv 2605.24635 ↗First posted 23 May 2026cs.CLcited by 0

On the map: LLM reasoning → Clinical and biomedical applications

Abstract (arXiv)

Medical large language models hold promise for reducing healthcare disparities, yet Hindi remains severely underrepresented. While medical LLMs excel in high-resource languages, their performance degrades sharply in Hindi, particularly on Indian systems of medicine. We argue that robust cross-lingual medical transfer requires Hindi reasoning. To this end, we introduce HiMed, a Hindi reasoning medical corpus and benchmark suite covering both Western and Indian medicine. We further propose HiMed-8B, a Hindi-form medical reasoning LLM, through the design of decaying scaffolding reward. Extensive experiments demonstrate improvement in Hindi medical reasoning performance and a reduction in the English-Hindi accuracy gap. Ablation studies validate the contribution of each training stage and reward component. All code, data, and weights are available

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 54 of its 126 references that are in the map. First posted on arXiv 23 May 2026.

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54 of 126 references.

Closest ancestors · 4

Same direction, newest first

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  3. 2025MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs1 Apr
  4. 2025Citrus: Leveraging Expert Cognitive Pathways in a Medical Language Model for Advanced Medical Decision Support25 Feb

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