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SOTA RAG Systems Today Over the last year, RAG has evolved dramatically, and most SOTA systems today support - Multi-modal documents and responses - LLM routing to different LLMs based on the complexity of the query - Multi-lingual requests and response - Increased accuracy and reduced hallucination with verification steps - Feedback and monitoring of the system in production A clever approach was proposed recently called Speculative RAG. This framework leverages a larger generalist LM to efficiently verify multiple RAG drafts produced in parallel by a smaller, distilled specialist LM. Each draft is generated from a distinct subset of retrieved documents, offering diverse perspectives on the evidence while reducing input token counts per draft. This approach enhances comprehension of each subset and mitigates potential position bias over an extended context. Their method accelerates RAG by delegating drafting to the smaller specialist LM, with the larger generalist LM performing a single verification pass over the drafts. Speculative RAG enhances accuracy by up to 12.97% while reducing latency by 51% compared to conventional RAG systems on PubHealth. Approaches like this have helped solve complex RAG problems.

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