mlsanityData to 14 Oct 2026

MedChatZH: a Better Medical Adviser Learns from Better Instructions

arXiv 2309.01114 ↗First posted 3 Sep 2023cs.CL cs.AIcited by 8

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Abstract (arXiv)

Generative large language models (LLMs) have shown great success in various applications, including question-answering (QA) and dialogue systems. However, in specialized domains like traditional Chinese medical QA, these models may perform unsatisfactorily without fine-tuning on domain-specific datasets. To address this, we introduce MedChatZH, a dialogue model designed specifically for traditional Chinese medical QA. Our model is pre-trained on Chinese traditional medical books and fine-tuned with a carefully curated medical instruction dataset. It outperforms several solid baselines on a real-world medical dialogue dataset. We release our model, code, and dataset on https://github.com/tyang816/MedChatZH to facilitate further research in the domain of traditional Chinese medicine and LLMs.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 15 of its 23 references that are in the map. First posted on arXiv 3 Sep 2023.

Builds on

15 of 23 references.

References · 15

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2020Language Models are Few-Shot Learnerscited by 32,419
  4. 2022Training language models to follow instructions with human feedbackcited by 15,971
  5. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  6. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  7. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,984
  8. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  9. 2021GLM: General Language Model Pretraining with Autoregressive Blank Infillingcited by 1,031
  10. 2022GLM-130B: An Open Bilingual Pre-trained Modelcited by 843
  11. 2023Efficient and Effective Text Encoding for Chinese LLaMA and Alpacacited by 305
  12. 2023HuatuoGPT, towards Taming Language Model to Be a Doctorcited by 214
3 more
  1. 2023HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledgecited by 162
  2. 2023Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Casescited by 86
  3. 2021On the Evaluation of Neural Code Summarizationcited by 48

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 2; 2025: 3.

8 papers.

  1. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 316
  2. 2023Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificitycited by 206
  3. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 163
  4. 2024A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicinecited by 45
  5. 2025A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontierscited by 37
  6. 2025Benchmarking Large Language Models on Multiple Tasks in Bioinformatics NLP with Promptingcited by 8
  7. 2024CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimizationcited by 5
  8. 2025DoPI: Doctor-like Proactive Interrogation LLM for Traditional Chinese Medicinecited by 1