3 citations · 6 across the 5 of their papers we have counts for
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cs.DC2024
CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration
Hongpeng Jin, Yanzhao Wu
Large Language Models (LLMs) exhibit remarkable human-like predictive capabilities. However, it is challenging to deploy LLMs to provide efficient and adaptive inference services a…
cs.LG2024★ 1 cited
Boosting Deep Ensembles with Learning Rate Tuning
Hongpeng Jin, Yanzhao Wu
The Learning Rate (LR) has a high impact on deep learning training performance. A common practice is to train a Deep Neural Network (DNN) multiple times with different LR policies…
cs.LG2024★ 2 cited
DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models
Maryam Akhavan Aghdam, Hongpeng Jin, Yanzhao Wu
Transformer-based Mixture-of-Experts (MoE) models have been driving several recent technological advancements in Natural Language Processing (NLP). These MoE models adopt a router…