AI RESEARCH
SRAG: RAG with Structured Data Improves Vector Retrieval
arXiv CS.CL
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ArXi:2603.26670v1 Announce Type: cross Retrieval Augmented Generation (RAG) provides the necessary informational grounding to LLMs in the form of chunks retrieved from a vector database or through web search. RAG could also use knowledge graph triples as a means of providing factual information to an LLM. However, the retrieval is only based on representational similarity between a question and the contents. The performance of RAG depends on the numeric vector representations of the query and the chunks.