CAG is an efficient and simple alternative to RAG for enhancing the caching mechanism of generative models.
CAG (Cache-Augmented Generation) is a method used to enhance generative models by utilizing caches during the generation process to improve efficiency and performance. Compared to RAG (Retrieval-Augmented Generation), CAG offers a simpler and more direct approach to optimizing the model's response speed and output quality through caching mechanisms. This method is suitable for scenarios that require fast responses and high-quality generated content, such as chatbots and content generation.
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