mlsanityData to 14 Oct 2026

MRAG: Benchmarking Retrieval-Augmented Generation for Bio-medicine

arXiv 2601.16503 ↗First posted 23 Jan 2026cs.CL cs.AIcited by 4

On the map: Retrieval-augmented generation → Medical and biomedical RAG

Abstract (arXiv)

While Retrieval-Augmented Generation (RAG) has been swiftly adopted in scientific and clinical QA systems, a comprehensive evaluation benchmark in the medical domain is lacking. To address this gap, we introduce the Medical Retrieval-Augmented Generation (MRAG) benchmark, covering various tasks in English and Chinese languages, and building a corpus with Wikipedia and Pubmed. Additionally, we develop the MRAG-Toolkit, facilitating systematic exploration of different RAG components. Our experiments reveal that: (a) RAG enhances LLM reliability across MRAG tasks. (b) the performance of RAG systems is influenced by retrieval approaches, model sizes, and prompting strategies. (c) While RAG improves usefulness and reasoning quality, LLM responses may become slightly less readable for long-form questions. We will release the MRAG-Bench's dataset and toolkit with CCBY-4.0 license upon acceptance, to facilitate applications from both academia and industry.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 49 of its 111 references that are in the map. First posted on arXiv 23 Jan 2026.

Builds on

49 of 111 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Benchmarking Retrieval-Augmented Generation for Medicine20 Feb
  2. 2023Almanac: Retrieval-Augmented Language Models for Clinical Medicine1 Mar

Other references · 47

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  4. 2020Measuring Massive Multitask Language Understandingcited by 7,963
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  12. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
35 more
  1. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,288
  2. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,252
  3. 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,184
  4. 2022Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learningcited by 896
  5. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  6. 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Modelscited by 708
  7. 2023In-Context Retrieval-Augmented Language Modelscited by 702
  8. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  9. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 488
  10. 2023CMMLU: Measuring massive multitask language understanding in Chinesecited by 449
  11. 2023A Survey of Hallucination in Large Foundation Modelscited by 368
  12. 2023RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generationcited by 367
  13. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 354
  14. 2024RAFT: Adapting Language Model to Domain Specific RAGcited by 262
  15. 2024Capabilities of Gemini Models in Medicinecited by 237
  16. 2023MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrievalcited by 185
  17. 2023PaperQA: Retrieval-Augmented Generative Agent for Scientific Researchcited by 149
  18. 2023Unified Demonstration Retriever for In-Context Learningcited by 142
  19. 2023Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Healthcited by 118
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  21. 2023DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultationcited by 90
  22. 2023PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domaincited by 40
  23. 2024AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learningcited by 33
  24. 2021Literature-Augmented Clinical Outcome Predictioncited by 20
  25. 2024MiLoRA: Efficient Mixture of Low-Rank Adaptation for Large Language Models Fine-tuningcited by 19
  26. 2023F-PABEE: Flexible-patience-based Early Exiting for Single-label and Multi-label text Classification Taskscited by 18
  27. 2023Search Still Matters: Information Retrieval in the Era of Generative AIcited by 17
  28. 2025AMAS: Adaptively Determining Communication Topology for LLM-based Multi-Agent Systemcited by 15
  29. 2023Overview of the PromptCBLUE Shared Task in CHIP2023cited by 14
  30. 2023Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translationcited by 13
  31. 2022Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuningcited by 12
  32. 2024DRUM: Learning Demonstration Retriever for Large MUlti-modal Modelscited by 10
  33. 2025PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustmentcited by 9
  34. 2024PEDRO: Parameter-Efficient Fine-tuning with Prompt DEpenDent Representation MOdificationcited by 8
  35. 2025FT-MDT: Extracting Decision Trees from Medical Texts via a Novel Low-rank Adaptation Methodcited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026Evaluating ChatGPT on Medical Information Extraction Tasks: Performance, Explainability and Beyondcited by 1
  2. 2026Pursuing Best Industrial Practices for Retrieval-Augmented Generation in the Medical Domaincited by 1
  3. 2026ACL: Aligned Contrastive Learning Improves BERT and Multi-exit BERT Fine-tuningcited by 1
  4. 2026A Generative Model for Joint Multiple Intent Detection and Slot Fillingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
  2. 2024Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
  3. 2025Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights
  4. 2026When Retrieval Doesn't Help: A Large-Scale Study of Biomedical RAG
  5. 2026Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study
  6. 2024Rationale-Guided Retrieval Augmented Generation for Medical Question Answering
  7. 2024Development and Testing of Retrieval Augmented Generation in Large Language Models -- A Case Study Report
  8. 2025Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented Generation