Domain LLM

Domain-specific Large Language Models (LLMs) aim to adapt the power of general-purpose LLMs to specific domains, overcoming limitations like hallucinations and knowledge gaps. Current research focuses on methods like retrieval-augmented generation (RAG), incorporating knowledge graphs and vector stores to enhance accuracy and provide source attribution, as well as prompting strategies to improve performance on specific tasks, particularly in medical and legal domains. This work is significant because it addresses the high cost and time associated with fine-tuning LLMs for specialized applications, potentially leading to more efficient and effective deployment of LLMs across diverse fields.