58 citations · 120 across the 14 of their papers we have counts for
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cs.CL2023
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts
Ganesh Jawahar, Haichuan Yang, Yunyang Xiong +10
Weight-sharing supernets are crucial for performance estimation in cutting-edge neural architecture search (NAS) frameworks. Despite their ability to generate diverse subnetworks w…
cs.CL2021★ 1 cited
Noisy Training Improves E2E ASR for the Edge
Dilin Wang, Yuan Shangguan, Haichuan Yang +6
Automatic speech recognition (ASR) has become increasingly ubiquitous on modern edge devices. Past work developed streaming End-to-End (E2E) all-neural speech recognizers that can…