mlsanityData to 7 Oct 2026

RAG-BioQA: A Retrieval-Augmented Generation Framework for Long-Form Biomedical Question Answering

arXiv 2510.01612 ↗First posted 2 Oct 2025cs.CL cs.AIcited by 0

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

Abstract (arXiv)

The rapidly growth of biomedical literature creates challenges acquiring specific medical information. Current biomedical question-answering systems primarily focus on short-form answers, failing to provide comprehensive explanations necessary for clinical decision-making. We present RAG-BioQA, a retrieval-augmented generation framework for long-form biomedical question answering. Our system integrates BioBERT embeddings with FAISS indexing for retrieval and a LoRA fine-tuned FLAN-T5 model for answer generation. We train on 181k QA pairs from PubMedQA, MedDialog, and MedQuAD, and evaluate on a held-out PubMedQA test set. We compare four retrieval strategies: dense retrieval (FAISS), BM25, ColBERT, and MonoT5. Our results show that domain-adapted dense retrieval outperforms zero-shot neural re-rankers, with the best configuration achieving 0.24 BLEU-1 and 0.29 ROUGE-1. Fine-tuning improves BERTScore by 81% over the base model. We release our framework to support reproducible biomedical QA research.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 29 of its 49 references that are in the map. First posted on arXiv 2 Oct 2025.

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29 of 49 references.

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  1. 2024Benchmarking Retrieval-Augmented Generation for Medicine20 Feb

Other references · 28

  1. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  2. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  3. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  4. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,722
  5. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  6. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  7. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,404
  8. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  9. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,160
  10. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 786
  11. 2019ELI5: Long Form Question Answeringcited by 567
  12. 2022BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Miningcited by 531
16 more
  1. 2023Active Retrieval Augmented Generationcited by 506
  2. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 373
  3. 2022LinkBERT: Pretraining Language Models with Document Linkscited by 209
  4. 2023Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificitycited by 204
  5. 2021QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehensioncited by 91
  6. 2025Medical Hallucinations in Foundation Models and Their Impact on Healthcarecited by 89
  7. 2024BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Textcited by 85
  8. 2021KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answeringcited by 66
  9. 2021Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipelinecited by 65
  10. 2021Biomedical Question Answering: A Survey of Approaches and Challengescited by 46
  11. 2024PEDANTS: Cheap but Effective and Interpretable Answer Equivalencecited by 31
  12. 2025A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directionscited by 30
  13. 2025A comprehensive taxonomy of hallucinations in Large Language Modelscited by 18
  14. 2023Qlarify: Recursively Expandable Abstracts for Directed Information Retrieval over Scientific Paperscited by 8
  15. 2024Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answeringcited by 3
  16. 2023Top K Relevant Passage Retrieval for Biomedical Question Answeringcited by 2

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  1. 2025Efficient and Reproducible Biomedical Question Answering using Retrieval Augmented Generation
  2. 2026Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study
  3. 2025Beyond Retrieval: Ensembling Cross-Encoders and GPT Rerankers with LLMs for Biomedical QA
  4. 2026A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering
  5. 2025Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
  6. 2024Rationale-Guided Retrieval Augmented Generation for Medical Question Answering
  7. 2024BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A
  8. 2026When Retrieval Doesn't Help: A Large-Scale Study of Biomedical RAG