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Equation 36 · Part 2 · Naive, Graph, and Agentic: A Systems Comparison of RAG Architectures

Symbol L_enc

Ltotal=Lenc+∑i=1k(Lretrieve(i)+LLLM(i)).L_{\text{total}} = L_{\text{enc}} + \sum_{i=1}^{k} \left( L_{\text{retrieve}}^{(i)} + L_{\text{LLM}}^{(i)} \right).
LencL_{\text{enc}}

What this part means

the writing.

Its job in the formula

LeL_enc is one of the signed contributions combined to compute the quantity on the left.

Where the article explains it

Writing LencL_{\text{enc}} for query encoding, and Lretrieve(i)L_{\text{retrieve}}^{(i)} and LLLM(i)L_{\text{LLM}}^{(i)} for the retrieval and generation cost of round i , Ltotal=Lenc+∑i=1k(Lretrieve(i)+LLLM(i))L_{\text{total}} = L_{\text{enc}} + \sum_{i=1}^{k} \left( L_{\text{retrieve}}^{(i)} + L_{\text{LLM}}^{(i)} \right).

The passage around this formula

A single latency model makes the difference between the first three rows and the last two concrete. Writing LencL_{\text{enc}} for query encoding, and Lretrieve(i)L_{\text{retrieve}}^{(i)} and LLLM(i)L_{\text{LLM}}^{(i)} for the retrieval and generation cost of round i , Ltotal=Lenc+∑i=1k(Lretrieve(i)+LLLM(i))L_{\text{total}} = L_{\text{enc}} + \sum_{i=1}^{k} \left( L_{\text{retrieve}}^{(i)} + L_{\text{LLM}}^{(i)} \right). For naive and hybrid RAG, k = 1 by construction — the sum has exactly one term, and total latency is boundable in advance for any query.…

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