mlsanityData to 7 Oct 2026

AlpaCare:Instruction-tuned Large Language Models for Medical Application

arXiv 2310.14558 ↗First posted 23 Oct 2023cs.CL cs.AIcited by 88

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

Abstract (arXiv)

Instruction-finetuning (IFT) has become crucial in aligning Large Language Models (LLMs) with diverse human needs and has shown great potential in medical applications. However, previous studies mainly fine-tune LLMs on biomedical datasets with limited diversity, which often rely on benchmarks or narrow task scopes, and hence significantly limit the effectiveness on their medical instruction-following ability and generalizability. To bridge this gap, we propose creating a diverse, machine-generated medical IFT dataset, MedInstruct-52k, using GPT-4 and ChatGPT with a high-quality expert-curated seed set. We then fine-tune LLaMA-series models on the dataset to develop AlpaCare. Despite using a smaller domain-specific dataset than previous medical LLMs, AlpaCare not only demonstrates superior performance on medical applications, with up to 38.1% absolute gain over best baselines in medical free-form instruction evaluations, but also achieves 6.7% absolute gains averaged over multiple general domain benchmarks. Human evaluation further shows that AlpaCare consistently outperforms best baselines in terms of both correctness and helpfulness. We offer public access to our data, model, and codebase in https://github.com/XZhang97666/AlpaCare.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). Placed in Medical LLM alignment, one of 10 directions in LLM alignment / RLHF / preference optimisation. Builds on 21 of its 42 references that are in the map. First posted on arXiv 23 Oct 2023.

Builds on

21 of 42 references.

References · 21

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  3. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  4. 2016Overcoming catastrophic forgetting in neural networkscited by 4,718
  5. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
  6. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  7. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  8. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  9. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  10. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,271
  11. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,116
  12. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,023
9 more
  1. 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 883
  2. 2023Large Language Modelscited by 774
  3. 2021Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategiescited by 736
  4. 2023Instruction Tuning with GPT-4cited by 676
  5. 2023ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledgecited by 324
  6. 2023MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Datacited by 282
  7. 2019HEAD-QA: A Healthcare Dataset for Complex Reasoningcited by 100
  8. 2023INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language Modelscited by 62
  9. 2023Enhancing Small Medical Learners with Privacy-preserving Contextual Promptingcited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 43; 2025: 23; 2026: 19.

88 papers.

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  1. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 311
  2. 2024A Survey on Knowledge Distillation of Large Language Modelscited by 276
  3. 2024Continual Learning of Large Language Models: A Comprehensive Surveycited by 228
  4. 2023A Survey of Large Language Models in Medicine: Progress, Application, and Challengecited by 123
  5. 2024Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questionscited by 106
  6. 2024A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discoverycited by 96
  7. 2024A Closer Look at the Limitations of Instruction Tuningcited by 76
  8. 2024Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoningcited by 58
  9. 2024MedExQA: Medical Question Answering Benchmark with Multiple Explanationscited by 58
  10. 2024LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generationcited by 45
  11. 2024A Comprehensive Survey of Large Language Models and Multimodal Large Language Models in Medicinecited by 45
  12. 2024SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literaturecited by 37
38 more
  1. 2024MedAdapter: Efficient Test-Time Adaptation of Large Language Models towards Medical Reasoningcited by 35
  2. 2024Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Modelscited by 34
  3. 2025TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Recordscited by 33
  4. 2024Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoningcited by 31
  5. 2024Small Language Models Learn Enhanced Reasoning Skills from Medical Textbookscited by 30
  6. 2024SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domainscited by 28
  7. 2025A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcarecited by 27
  8. 2023BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processingcited by 25
  9. 2024A Benchmark for Long-Form Medical Question Answeringcited by 25
  10. 2024Causality for Large Language Modelscited by 24
  11. 2024PLLaMa: An Open-source Large Language Model for Plant Sciencecited by 22
  12. 2024LLMs Can Simulate Standardized Patients via Agent Coevolutioncited by 22
  13. 2025A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignmentcited by 20
  14. 2024Token-wise Influential Training Data Retrieval for Large Language Modelscited by 19
  15. 2025The Rise of Small Language Models in Healthcare: A Comprehensive Surveycited by 18
  16. 2024A Survey on Large Language Models from General Purpose to Medical Applications: Datasets, Methodologies, and Evaluationscited by 16
  17. 2024GP-VLS: A general-purpose vision language model for surgerycited by 16
  18. 2025Multimodal Large Language Models for Medicine: A Comprehensive Surveycited by 16
  19. 2024Efficient Knowledge Infusion via KG-LLM Alignmentcited by 13
  20. 2024Large Language Models in the Clinic: A Comprehensive Benchmarkcited by 12
  21. 2025Bottom-up Domain-specific Superintelligence: A Reliable Knowledge Graph is What We Needcited by 12
  22. 2024KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Servercited by 11
  23. 2024Me LLaMA: Foundation Large Language Models for Medical Applicationscited by 10
  24. 2024ReadCtrl: Personalizing text generation with readability-controlled instruction learningcited by 10
  25. 2026F2LLM-v2: Inclusive, Performant, and Efficient Embeddings for a Multilingual Worldcited by 10
  26. 2024A Middle Path for On-Premises LLM Deployment: Preserving Privacy Without Sacrificing Model Confidentialitycited by 8
  27. 2024MedINST: Meta Dataset of Biomedical Instructionscited by 7
  28. 2025A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Modelscited by 7
  29. 2024Clinical Insights: A Comprehensive Review of Language Models in Medicinecited by 6
  30. 2025Supervised Optimism Correction: Be Confident When LLMs Are Surecited by 5
  31. 2024Aqulia-Med LLM: Pioneering Full-Process Open-Source Medical Language Modelscited by 4
  32. 2024AlpaPICO: Extraction of PICO Frames from Clinical Trial Documents Using LLMscited by 4
  33. 2024Knowledge-Augmented Multimodal Clinical Rationale Generation for Disease Diagnosis with Small Language Modelscited by 4
  34. 2026Health-ORSC-Bench: A Benchmark for Measuring Over-Refusal and Safety Completion in Health Contextcited by 4
  35. 2024PPFedIT: Towards Privacy-Preserving Federated Instruction Tuning with Few-shot Local Examplescited by 3
  36. 2025Dialogue is Better Than Monologue: Instructing Medical LLMs via Strategical Conversationscited by 3
  37. 2025Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?cited by 3
  38. 2025Balancing Truthfulness and Informativeness with Uncertainty-Aware Instruction Fine-Tuningcited by 3

50 most cited of 88 All 88 (JSON)

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  1. 2023MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
  2. 2024Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Data
  3. 2025Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
  4. 2025MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
  5. 2024MedCare: Advancing Medical LLMs through Decoupling Clinical Alignment and Knowledge Aggregation
  6. 2026Assessing Large Language Models for Medical QA: Zero-Shot and LLM-as-a-Judge Evaluation
  7. 2024A Spectrum Evaluation Benchmark for Medical Multi-Modal Large Language Models
  8. 2025IIMedGPT: Promoting Large Language Model Capabilities of Medical Tasks by Efficient Human Preference Alignment