QuoVLA: Quotient Space for Vision-Language-Action Models 事件

QuoVLA: Quotient Space for Vision-Language-Action Models arXiv:2605.24890v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models commonly adapt pretrained Vision-Language Models (VLMs) to robot control by mapping visual observations and language instructions to continuous actions. Existing approaches typically take an action-insufficiency view, assuming that pretrained VLM latents either lack directly usable action information or should be shielded from action-learning signals. Agai