3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.LG2023★ 3 cited
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs
Jintang Li, Sheng Tian, Ruofan Wu +6
The prevalence of large-scale graphs poses great challenges in time and storage for training and deploying graph neural networks (GNNs). Several recent works have explored solution…
cs.CV2023
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Segmentation
Lianghui Zhu, Yingyue Li, Jiemin Fang +4
Transformer has been very successful in various computer vision tasks and understanding the working mechanism of transformer is important. As touchstones, weakly-supervised semanti…