深慢Shimmer 深慢Shimmer arXiv:2606.30686v1 Announce Type: new Abstract: Vision-Language-Action (VLA) systems, built on pretrained vision-language models (VLMs), have shown rapidly improving performance on robot manipulation benchmarks. These gains are commonly interpreted as evidence that semantic representations learned from internet-scale data transfer to physical execution generalization. This position paper argues that the assumption underlying this interpretation -- that semantic generalization is sufficient to su
This position paper provides a high-alpha critique of the current VLA hype, arguing that success metrics are flawed and don't prove physical reasoning. It is highly actionable for researchers designing next-gen robotics benchmarks.