A paper on arXiv introduces Velox, a training-free attention router that selects context at the token-block level using camera frustum slab correspondences from streaming geometry, aiming to cut the growing KV-cache cost of chunked video diffusion world models as rollouts lengthen. The authors report a 4.36x attention speedup and 2.43x denoising speedup at chunk 48, and a gap of within 0.15 average points versus the dense LingBot-Fast-Cam baseline across the full 158-case WBench navigation split. The work is by Qiuhong Shen, Shizun Wang and Xinchao Wang; all figures are author-reported and have not been independently verified.