arXiv AI By Khanh D. Nguyen, Hoang M. Truong, An T. Le

vla.simd: Efficient CPU Inference for Language-Conditioned Manipulation

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arXiv AI
Aug 18

Algorithm-Architecture Co-Design for Efficient VLA Inference via Speculative Inference and Verification

arXiv:2608. 15636v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in the field of embodied AI, but their high computational cost and limited predicted action length hinder real-time deployment.

By Chunyu Qi, Zhuoran Song, Jian Weng, Haozhe Jiang, Xueyuan Liu, Naifeng Jing, Guanghui He, Xiaoyao Liang, Haibing Guan
arXiv AI
Sep 17

rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

The paper introduces rMuscle, a real‑time Vision‑Language‑Action inference framework that mimics human muscle memory to accelerate robotic decision making. By exploiting repeated task similarity, rMuscle uses a dual‑phase cache: a Context Cache reuses visual‑token outputs and an Action Cache reuses neuron activation patterns, reducing computation and weight accesses. Experiments on RTX 4090 and Jetson Thor show 1.29–1.42× speedups on LIBERO, RoboTwin, and physical manipulation tasks while preserving success rates on real robots.

By Kaijun Zhou, Zhiyang Li, Le Chen, Jinyu Gu