What is the correlation between privacy budget epsilon and inference latency for LLaMA-2 when evaluated on the

Abstract

Abstract: We find arithmetic ability resides within a limited number of attention heads, with each head specializing in distinct operations. To delve into the reason, we introduce the Comparative Neuron Analysis (CNA) method, which identifies an internal logic chain consisting of four distinct stages from input to prediction: feature enhancing with shallow FFN neurons, feature transferring by shallow attention layers, feature predicting by arithmetic heads, and prediction enhancing among deep FFN neurons. Moreover, we identify the human-interpretable FFN neurons within both feature-enhancing and feature

Research Question

What is the correlation between privacy budget epsilon and inference latency for LLaMA-2 when evaluated on the SVAMP benchmark?

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