Self-attention is required. The model must contain at least one self-attention layer. This is the defining feature of a transformer — without it, you have an MLP or RNN, not a transformer.
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The pruned nodes (in red) represent entire regions of space that the algorithm never examines. The points inside those regions are never checked. Compare the "Nodes Visited" count to the total number of points. The quadtree is doing far less work than a brute-force scan.