Why Does Train-Validation Separation Emerge? Update-Pressure Density Dynamics in Pretrained Backbones

Excerpt

arXiv:2610.01425v1 Announce Type: new Abstract: Train-validation separation is the evolving difference between performance on observed training examples and a finite held-out validation set. We propose a dynamic structural account of how this gap develops during adaptation of pretrained models: continued fitting can shift update demand from broadly reusable support toward narrower support with weaker held-out transfer. A conditional local model links this shift to increasing heterogeneity in gra