Output-Level Regularization Eliminates the Seed Lottery in Single-GPU VLA Fine-Tuning

arXiv:2606.13856v1 Announce Type: new Abstract: Fine-tuning a vision-language-action model (VLA-JEPA) on a single GPU should be simple: load a pretrained checkpoint, run training, deploy. There is a hidden danger. Run the same fine-tuning code thirteen times -- same data, same architecture, differe