mlsanityData to 14 Oct 2026

ChiMed 2.0: Advancing Chinese Medical Dataset in Facilitating Large Language Modeling

arXiv 2507.15275 ↗First posted 21 Jul 2025cs.CLcited by 0

On the map: LLM alignment / RLHF / preference optimisation → Medical LLM alignment

Abstract (arXiv)

Building high-quality data resources is crucial for advancing artificial intelligence research and applications in specific domains, particularly in the Chinese medical domain. Existing Chinese medical datasets are limited in size and narrow in domain coverage, falling short of the diverse corpora required for effective pre-training. Moreover, most datasets are designed solely for LLM fine-tuning and do not support pre-training and reinforcement learning from human feedback (RLHF). In this paper, we propose a Chinese medical dataset named ChiMed 2.0, which extends our previous work ChiMed, and covers data collected from Chinese medical online platforms and generated by LLMs. ChiMed 2.0 contains 204.4M Chinese characters covering both traditional Chinese medicine classics and modern general medical data, where there are 164.8K documents for pre-training, 351.6K question-answering pairs for supervised fine-tuning (SFT), and 41.7K preference data tuples for RLHF. To validate the effectiveness of our approach for training a Chinese medical LLM, we conduct further pre-training, SFT, and RLHF experiments on representative general domain LLMs and evaluate their performance on medical benchmark datasets. The results show performance gains across different model scales, validating the dataset's effectiveness and applicability.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical LLM alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 24 of its 41 references that are in the map. First posted on arXiv 21 Jul 2025.

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24 of 41 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023ChiMed-GPT: A Chinese Medical Large Language Model with Full Training Regime and Better Alignment to Human Preferences10 Nov
  2. 2023Zhongjing: Enhancing the Chinese Medical Capabilities of Large Language Model through Expert Feedback and Real-world Multi-turn Dialogue7 Aug

Other references · 22

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10 more
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  4. 2025MedBench v4: A Robust and Scalable Benchmark for Evaluating Chinese Medical Language Models, Multimodal Models, and Intelligent Agents
  5. 2025MTCMB: A Multi-Task Benchmark Framework for Evaluating LLMs on Knowledge, Reasoning, and Safety in Traditional Chinese Medicine
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  7. 202547B Mixture-of-Experts Beats 671B Dense Models on Chinese Medical Examinations
  8. 2025TCM-Eval: An Expert-Level Dynamic and Extensible Benchmark for Traditional Chinese Medicine