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Merging transformers sequentially along their execution path, rather than layer-by-layer, dramatically reduces error accumulation and unlocks principled multi-task capacity expansion.
Local SGD's efficiency can be rigorously explained through bounded second-order heterogeneity, revealing nearly tight convergence rates for general convex objectives.
