arXiv:2605.22940v1 Announce Type: cross Abstract: Deep learning is increasingly viewed as a dynamical process in parameter space, yet many existing theories still treat training
arXiv:2603.15678v2 Announce Type: replace-cross Abstract: Despite hundreds of millions of parameters, transformer training trajectories evolve within only a few coherent
arXiv:2605.04115v1 Announce Type: cross Abstract: Learning in neural systems arises from synaptic changes that reshape the representations underlying behavior. While low-rank
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