IEEE

Towards Retrieval-Augmented Large Language Models: Data Management and System Design

Abstract: Retrieval-augmented generation (RAG) has become a transformative approach for enhancing large language models (LLMs) by integrating external, reliable, and up-to-date knowledge. This ...
IEEE

Efficient Vector-Multiplicative Privacy-Preserving Retrieval-Augmented Generation for Large Language Models

Abstract: Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external knowledge, yet it is faces a fundamental trade-off between knowledge confidentiality and retrieval ...
Journal of Medical Internet Research

Improving Retrieval Augmented Generation for Health Care by Fine-Tuning Clinical Embedding Models: Development and Evaluation Study

Background: Embedding models are critical components of Retrieval Augmented Generation (RAG) systems for retrieving and searching unstructured medical data. However, existing models are predominantly ...