mlsanityData to 7 Oct 2026

SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?

arXiv 2502.13233 ↗First posted 18 Feb 2025cs.CL cs.AI cs.IRcited by 9

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Abstract (arXiv)

Large Language Models (LLMs) have shown remarkable capabilities in general domains but often struggle with tasks requiring specialized knowledge. Conventional Retrieval-Augmented Generation (RAG) techniques typically retrieve external information from static knowledge bases, which can be outdated or incomplete, missing fine-grained clinical details essential for accurate medical question answering. In this work, we propose SearchRAG, a novel framework that overcomes these limitations by leveraging real-time search engines. Our method employs synthetic query generation to convert complex medical questions into search-engine-friendly queries and utilizes uncertainty-based knowledge selection to filter and incorporate the most relevant and informative medical knowledge into the LLM's input. Experimental results demonstrate that our method significantly improves response accuracy in medical question answering tasks, particularly for complex questions requiring detailed and up-to-date knowledge.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 28 of its 44 references that are in the map. First posted on arXiv 18 Feb 2025.

Builds on

28 of 44 references.

References · 28

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2024The Llama 3 Herd of Modelscited by 14,192
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  5. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  6. 2020The Pile: An 800GB Dataset of Diverse Text for Language Modelingcited by 2,346
  7. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  8. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  9. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  10. 2024Large Language Monkeys: Scaling Inference Compute with Repeated Samplingcited by 946
  11. 2022MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answeringcited by 525
  12. 2024Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexitycited by 437
16 more
  1. 2023Making Retrieval-Augmented Language Models Robust to Irrelevant Contextcited by 364
  2. 2019KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representationcited by 356
  3. 2024Benchmarking Retrieval-Augmented Generation for Medicinecited by 326
  4. 2024BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domainscited by 299
  5. 2024The Power of Noise: Redefining Retrieval for RAG Systemscited by 275
  6. 2023MEDITRON-70B: Scaling Medical Pretraining for Large Language Modelscited by 272
  7. 2023Query Rewriting for Retrieval-Augmented Large Language Modelscited by 211
  8. 2024InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationalescited by 100
  9. 2024ChatQA: Surpassing GPT-4 on Conversational QA and RAGcited by 90
  10. 2024Instruction Pre-Training: Language Models are Supervised Multitask Learnerscited by 63
  11. 2024Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questionscited by 54
  12. 2024Rationale-Guided Retrieval Augmented Generation for Medical Question Answeringcited by 41
  13. 2024SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domainscited by 28
  14. 2024Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question Answeringcited by 20
  15. 2024UncertaintyRAG: Span-Level Uncertainty Enhanced Long-Context Modeling for Retrieval-Augmented Generationcited by 14
  16. 2024Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domaincited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 5.

9 papers.

  1. 2025Can Knowledge-Graph-based Retrieval Augmented Generation Really Retrieve What You Need?cited by 8
  2. 2025CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysiscited by 6
  3. 2025Build AI Assistants using Large Language Models and Agents to Enhance the Engineering Education of Biomechanicscited by 1
  4. 2025From Retrieval to Generation: Unifying External and Parametric Knowledge for Medical Question Answeringcited by 0
  5. 2026UETQuintet at BioCreative IX -- MedHopQA: Enhancing Biomedical QA with Selective Multi-hop Reasoning and Contextual Retrievalcited by 0
  6. 2026Less Data Approximates More: Earning Faithful Confidence in High-Stakes Domainscited by 0
  7. 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modescited by 0
  8. 2026TRACE: Agentic Catalog Enrichment with Multi-source Evidence Groundingcited by 0
  9. 2026Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
  2. 2026A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering
  3. 2025Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
  4. 2025MedBioRAG: Semantic Search and Retrieval-Augmented Generation with Large Language Models for Medical and Biological QA
  5. 2024Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
  6. 2025AR-Med: Automated Relevance Enhancement in Medical Search via LLM-Driven Information Augmentation
  7. 2024JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability
  8. 2024The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA