News / EDA & Tools / Efficient VLA Inference via Retrieval-Based Speculation and Hardware Acceleration
Efficient VLA Inference via Retrieval-Based Speculation and Hardware Acceleration
By The Semiconductor Hub news desk ·
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Vision-language-action (VLA) models enable robots to understand and execute complex instructions, but their autoregressive (AR) action generation introduces significant latency on resource-constrained robotic platforms. Speculative decoding can accelerate AR-based inference by parallelizing action generation and verification; however, existing approaches rely on costly draft models, which are inefficient on edge platforms. In this paper, we propose Zora, a hardware-software co-design framework …
Read at arXiv cs.AR (Hardware Architecture)Source: arXiv cs.AR (Hardware Architecture), published . The summary is the Hub's own; the full story is at the source. Report a rights or accuracy concern