Retrieval-Augmented Generation, or RAG, marks an important step forward for natural language processing. It helps large language models (LLMs) perform better by letting them check information outside their training data before creating a response. This means LLMs can work well with specific company knowledge or new information without costly retraining. Rerankers for RAG play a […]The post Top 7 Rerankers for RAG appeared first on Analytics Vidhya.