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20192022
most citedGLaM: Efficient Scaling of Language Models with Mixture-of-Experts

169 citations · 480 across the 9 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

eess.IV2021★ 15 cited

MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification

Jingye Chen, Jieneng Chen, Zongwei Zhou +3

Recent advances in automated skin cancer diagnosis have yielded performance on par with board-certified dermatologists. However, these approaches formulated skin cancer diagnosis a…

cs.CL2021★ 169 cited

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

Nan Du, Yanping Huang, Andrew M. Dai +24

Scaling language models with more data, compute and parameters has driven significant progress in natural language processing. For example, thanks to scaling, GPT-3 was able to ach…

cs.CV2021★ 9 cited

Learning from Temporal Gradient for Semi-supervised Action Recognition

Junfei Xiao, Longlong Jing, Lin Zhang +5

Semi-supervised video action recognition tends to enable deep neural networks to achieve remarkable performance even with very limited labeled data. However, existing methods are m…

eess.IV2021

Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection

Nahid Ul Islam, Shiv Gehlot, Zongwei Zhou +2

Pulmonary embolism (PE) represents a thrombus ("blood clot"), usually originating from a lower extremity vein, that travels to the blood vessels in the lung, causing vascular obstr…

eess.AS2021★ 164 cited

BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition

Yu Zhang, Daniel S. Park, Wei Han +23

We summarize the results of a host of efforts using giant automatic speech recognition (ASR) models pre-trained using large, diverse unlabeled datasets containing approximately a m…