Author

Zhuoran Song

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Jul 2026

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference

This paper proposes VQVLA, an algorithm-hardware co-design framework that accelerates VLA inference by exploiting weight similarity and execution dynamics, and proposes a merged-centroid vectorized GEMM paradigm that operates on the codebook-index representation.

Zhuoran Song, Haozhe Jiang, Chunyu Qi et al. · arXiv.org · 0 citations

Preprint Aug 2026

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

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. Although Dadu-Corki, a dedicated accelerator for efficient embodied AI, has been introduced, it does not exploit t...

Chunyu Qi, Zhuoran Song, Jian Weng et al. · 0 citations