The Universal Weight Subspace Hypothesis

Excerpt

arXiv:2512.05117v3 Announce Type: replace-cross Abstract: We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale empirical evidence that demonstrates that neural networks systematically converge to shared spectral subspaces regardless of initialization, task, or domain. Through mode-wise spectral analysis of over 1200 models - including 500 Mistral-7B LoRAs, 500 Vision Transformers, and 50 L