RAG (Retrieve, Augment, Generate)

RAG is a framework used to fine-tune language models, such as those used in AI for HR recruiting, to improve their performance on specific tasks. The framework consists of three stages: Retrieve, Augment, and Generate. In the Retrieve stage, the model retrieves relevant information from a database or knowledge graph. In the Augment stage, the model augments the retrieved information with additional context or data. In the Generate stage, the model generates a response or output based on the augmented information. RAG has been shown to improve the performance of language models on a variety of tasks, including question answering, text classification, and language translation.