AINeutralarXiv – CS AI · 10h ago6/10
🧠
Assessment of RAG and Fine-Tuning for Industrial Question-Answering-Applications
A new study compares Retrieval-Augmented Generation (RAG) and fine-tuning approaches for adapting Large Language Models to enterprise question-answering tasks in the automotive industry. The research finds that RAG offers superior cost-efficiency while maintaining comparable answer quality, even enabling open-source models to match premium model performance.