This is the fourth installment in a multi-part series on evaluating various RAG systems using Tonic Validate, a RAG ...

为了最大限度地发挥效果，使用 rag 的 llm 还需要连接到部门希望提取数据的来源 - 如客户服务平台、内容管理系统和人力资源系统等。这类集成需要 ...

检索增强生成（RAG）在开放域问答任务中表现出色。然而，传统搜索引擎可能会检索浅层内容，限制了大型语言模型（LLM）处理复杂、多层次信息的能力。为了解决这个问题，我们引入了WebWalkerQA，一个旨在评估LLM执行网页遍历能力的基准。它评估LLM ...

As LLMs become more capable, many RAG applications can be replaced with cache-augmented generation that include documents in the prompt.

RAG is changing the face of generative AI by aggregating retrieval and generation to bring out precise, pertinent and ...

This ‘grounding’ of an LLM means effectively bypassing it and running the system more like a traditional ... Of course, in the Facebook paper it is noted that RAG-enhanced LLMs are still ...

RAG takes large language models a step further by drawing on trusted sources of domain-specific information. This brings ...

The retrieval system finds relevant information in a knowledge ... be used for the initial training of the LLM. RAG is particularly useful for any generative AI applications that work within ...

The Contextual AI Platform provides access to all three of the main components needed to build a RAG system, including the underlying LLM that responds to questions, a “retriever” module that ...