mlsanityData to 7 Oct 2026

BiomedRAG: A Retrieval Augmented Large Language Model for Biomedicine

arXiv 2405.00465 ↗First posted 1 May 2024cs.CLcited by 30

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

Abstract (arXiv)

Large Language Models (LLMs) have swiftly emerged as vital resources for different applications in the biomedical and healthcare domains; however, these models encounter issues such as generating inaccurate information or hallucinations. Retrieval-augmented generation provided a solution for these models to update knowledge and enhance their performance. In contrast to previous retrieval-augmented LMs, which utilize specialized cross-attention mechanisms to help LLM encode retrieved text, BiomedRAG adopts a simpler approach by directly inputting the retrieved chunk-based documents into the LLM. This straightforward design is easily applicable to existing retrieval and language models, effectively bypassing noise information in retrieved documents, particularly in noise-intensive tasks. Moreover, we demonstrate the potential for utilizing the LLM to supervise the retrieval model in the biomedical domain, enabling it to retrieve the document that assists the LM in improving its predictions. Our experiments reveal that with the tuned scorer,textsc BiomedRAG attains superior performance across 5 biomedical NLP tasks, encompassing information extraction (triple extraction, relation extraction), text classification, link prediction, and question-answering, leveraging over 9 datasets. For instance, in the triple extraction task, textscBiomedRAG outperforms other triple extraction systems with micro-F1 scores of 81.42 and 88.83 on GIT and ChemProt corpora, respectively.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 27 of its 46 references that are in the map. First posted on arXiv 1 May 2024.

Builds on

27 of 46 references.

References · 27

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 2,126
  4. 2022Survey of Hallucination in Natural Language Generationcited by 2,056
  5. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  6. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  7. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  8. 2021Improving language models by retrieving from trillions of tokenscited by 1,278
  9. 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 788
  10. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  11. 2022Galactica: A Large Language Model for Sciencecited by 736
  12. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
15 more
  1. 2023In-Context Retrieval-Augmented Language Modelscited by 694
  2. 2022RARR: Researching and Revising What Language Models Say, Using Language Modelscited by 286
  3. 2023ToolQA: A Dataset for LLM Question Answering with External Toolscited by 273
  4. 2022Unified Structure Generation for Universal Information Extractioncited by 220
  5. 2023A Study of Generative Large Language Model for Medical Research and Healthcarecited by 160
  6. 2023Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Surveycited by 134
  7. 2020Drug Repurposing for COVID-19 via Knowledge Graph Completioncited by 30
  8. 2022OneRel:Joint Entity and Relation Extraction with One Module in One Stepcited by 27
  9. 2022UniRel: Unified Representation and Interaction for Joint Relational Triple Extractioncited by 14
  10. 2023How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domaincited by 14
  11. 2023Diverse Retrieval-Augmented In-Context Learning for Dialogue State Trackingcited by 10
  12. 2022A Hierarchical N-Gram Framework for Zero-Shot Link Predictioncited by 9
  13. 2023Understand the Dynamic World: An End-to-End Knowledge Informed Framework for Open Domain Entity State Trackingcited by 8
  14. 2023Easy-to-Hard Learning for Information Extractioncited by 5
  15. 2024A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Modelscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 17; 2026: 7.

30 papers.

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  1. 2025Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Surveycited by 47
  2. 2024A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directionscited by 34
  3. 2025Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoningcited by 33
  4. 2024RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Modelscited by 24
  5. 2025MatSciBench: Benchmarking the Reasoning Ability of Large Language Models in Materials Sciencecited by 15
  6. 2024CancerLLM: A Large Language Model in Cancer Domaincited by 11
  7. 2024Benchmarking Retrieval-Augmented Large Language Models in Biomedical NLP: Application, Robustness, and Self-Awarenesscited by 10
  8. 2025RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Modelscited by 6
  9. 2025BioMedSearch: A Multi-Source Biomedical Retrieval Framework Based on LLMscited by 4
  10. 2025GraPPI: A Retrieve-Divide-Solve GraphRAG Framework for Large-scale Protein-protein Interaction Explorationcited by 3
  11. 2025HealthContradict: Evaluating Biomedical Knowledge Conflicts in Language Modelscited by 3
  12. 2025Knowledge-Augmented Long-CoT Generation for Complex Biomolecular Reasoningcited by 2
18 more
  1. 2025Can Frontier LLMs Replace Annotators in Biomedical Text Mining? Analyzing Challenges and Exploring Solutionscited by 1
  2. 2025RAD: Towards Trustworthy Retrieval-Augmented Multi-modal Clinical Diagnosiscited by 1
  3. 2025CliniBench: A Clinical Outcome Prediction Benchmark for Generative and Encoder-Based Language Modelscited by 1
  4. 2026An Alternative Trajectory for Generative AIcited by 1
  5. 2026Injecting Structured Biomedical Knowledge into Language Models: Continual Pretraining vs. GraphRAGcited by 1
  6. 2024Detecci'on Autom'atica de Patolog'ias en Notas Cl'inicas en Espa~nol Combinando Modelos de Lenguaje y Ontolog'ias M'edicoscited by 0
  7. 2024Automatic detection of diseases in Spanish clinical notes combining medical language models and ontologiescited by 0
  8. 2025Conversational Text Extraction with Large Language Models Using Retrieval-Augmented Systemscited by 0
  9. 2025Biomedical Question Answering via Multi-Level Summarization on a Local Knowledge Graphcited by 0
  10. 2025Error-Aware Curriculum Learning for Biomedical Relation Classificationcited by 0
  11. 2025BRAINCELL-AID: An Agentic AI Created Brain Cell Type Resource for Community Annotationcited by 0
  12. 2025CareMedEval dataset: Evaluating Critical Appraisal and Reasoning in the Biomedical Fieldcited by 0
  13. 2025Biomedical Hypothesis Explainability with Graph-Based Context Retrievalcited by 0
  14. 2026Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Predictioncited by 0
  15. 2026UniD3: A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoningcited by 0
  16. 2026ANCHOR-RE: An Agentic Neuro-Symbolic Framework for Grounded Biomedical Relation Extractioncited by 0
  17. 2026Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generationcited by 0
  18. 2026DrugReason: Dynamic Multi-View Reasoning over Knowledge Graph and Language Evidence for Drug Repurposingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Improving Medical Reasoning through Retrieval and Self-Reflection with Retrieval-Augmented Large Language Models
  2. 2025Beyond Retrieval: Ensembling Cross-Encoders and GPT Rerankers with LLMs for Biomedical QA
  3. 2024A Review on Scientific Knowledge Extraction using Large Language Models in Biomedical Sciences
  4. 2025MedBioRAG: Semantic Search and Retrieval-Augmented Generation with Large Language Models for Medical and Biological QA
  5. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
  6. 2024A Survey for Large Language Models in Biomedicine
  7. 2026Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study
  8. 2024How do you know that? Teaching Generative Language Models to Reference Answers to Biomedical Questions