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This paper asks whether a second, temporally slower coupling-a slow sub-system operating on a temporally-downsampled view of the sequence and fed back into the fast path through a zero-initialised gate-complements it. The question is framed in the language of singularly perturbed ordinary differential equations (ODEs), where the fast variable $x$ evolves at the token rate, the slow variable $y$ evolves at one update per $P$ tokens, and the timescale ratio $\\varepsilon = 1/P$ is enforced structurally by causal block-mean pooling.\n  The paper instantiates the fast-slow ODE formalism as a concrete neural network: a fast path of standard causal attention over $T$ tokens, a slow path of full attention over $T/P$ pooled tokens ($P^2 \\times$ cheaper per layer), and a zero-initialised additive gate","title":"Attention is Just Another Name for Coupling?: A Fast-Slow ODE Perspective on Hierarchical Pretraining","url":"https://arxiv.org/abs/2606.16730","vendor":"arxiv_cs_ai"},"summary":"arXiv:2606.16730v1 Announce Type: cross \nAbstract: Causal self-attention is a coupling mechanism: each token's hidden state is updated by a learned mixture of preceding tokens at the same timescale. This paper asks whether a second, temporally slower coupling-a slow sub-system operating on a temporally-downsampled view of the sequence and fed back into the fast path through a zero-initialised gate-complements it. 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