mlsanityData to 7 Oct 2026

Leveraging Language Models and RAG for Efficient Knowledge Discovery in Clinical Environments

arXiv 2601.04209 ↗First posted 10 Dec 2025cs.CLcited by 0

Not on the map. Why?

Abstract (arXiv)

Large language models (LLMs) are increasingly recognized as valuable tools across the medical environment, supporting clinical, research, and administrative workflows. However, strict privacy and network security regulations in hospital settings require that sensitive data be processed within fully local infrastructures. Within this context, we developed and evaluated a retrieval-augmented generation (RAG) system designed to recommend research collaborators based on PubMed publications authored by members of a medical institution. The system utilizes PubMedBERT for domain-specific embedding generation and a locally deployed LLaMA3 model for generative synthesis. This study demonstrates the feasibility and utility of integrating domain-specialized encoders with lightweight LLMs to support biomedical knowledge discovery under local deployment constraints.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 20 references that are in the map. First posted on arXiv 10 Dec 2025.

Builds on

12 of 20 references.

References · 12

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  4. 2017Billion-scale similarity search with GPUscited by 2,477
  5. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,203
  6. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  7. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  8. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 996
  9. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 630
  10. 2023LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordinationcited by 48
  11. 2024Large Language Models for Automated Literature Review: An Evaluation of Reference Generation, Abstract Writing, and Review Compositioncited by 15
  12. 2024MedAide: Leveraging Large Language Models for On-Premise Medical Assistance on Edge Devicescited by 9

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2024Development and Testing of Retrieval Augmented Generation in Large Language Models -- A Case Study Report
  2. 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
  3. 2024A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models
  4. 2023Biomedical knowledge graph-optimized prompt generation for large language models
  5. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
  6. 2024Bailicai: A Domain-Optimized Retrieval-Augmented Generation Framework for Medical Applications
  7. 2024Federated Learning and RAG Integration: A Scalable Approach for Medical Large Language Models
  8. 2025ModernBERT + ColBERT: Enhancing biomedical RAG through an advanced re-ranking retriever