Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT
arXiv:2605.08879v1 Announce Type: new
Abstract: Unconstrained fine-tuning of flow-matching Vision-Language-Action (VLA) models drives dense parameter overwrites, degrading pre-trained capabilities. We present Conservative Supervised Fine-Tuning (ConSF…