1 citations · 1 across the 6 of their papers we have counts for
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From Inference Efficiency to Embodied Efficiency: Revisiting Efficiency Metrics for Vision-Language-Action Models
Zhuofan Li, Hongkun Yang, Zhenyang Chen +4
Vision-Language-Action (VLA) models have recently enabled embodied agents to perform increasingly complex tasks by jointly reasoning over visual, linguistic, and motor modalities.…
Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling
Chaojian Li, Zhifan Ye, Massimiliano Lupo Pasini +4
Atomistic materials modeling is a critical task with wide-ranging applications, from drug discovery to materials science, where accurate predictions of the target material property…
NetDistiller: Empowering Tiny Deep Learning via In-Situ Distillation
Shunyao Zhang, Yonggan Fu, Shang Wu +4
Boosting the task accuracy of tiny neural networks (TNNs) has become a fundamental challenge for enabling the deployments of TNNs on edge devices which are constrained by strict li…