The paper 'Hopfield networks are all you need' talks about why the softmax in the normal attention formulation is important for recall, and I'm always surprised its ideas haven't penetrated further in the community. Basically, viewing attention as a Hopfield network, there's a theoretical maximum number of patterns that, for linear functions, is actually very low, but for the exponential functions, you get very high information density and recall.