1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.DC2024
Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models
Wei Wang, Zhiquan Lai, Shengwei Li +5
The size of deep learning models has been increasing to enhance model quality. The linear increase in training computation budget with model size means that training an extremely l…
cs.LG2024
Accurate and Efficient Fine-Tuning of Quantized Large Language Models Through Optimal Balance
Ao Shen, Qiang Wang, Zhiquan Lai +2
Large Language Models (LLMs) have demonstrated impressive performance across various domains. However, the enormous number of model parameters makes fine-tuning challenging, signif…
cs.LG2021★ 1 cited
Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning
Ning Liu, Songlei Jian, Dongsheng Li +3
Graph neural networks (GNN) have been proven to be mature enough for handling graph-structured data on node-level graph representation learning tasks. However, the graph pooling te…