479 citations · 625 across the 22 of their papers we have counts for
4 papers · 1 filter
Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries
Xiao Liu, Shiyu Zhao, Kai Su +6
Knowledge graph (KG) embeddings have been a mainstream approach for reasoning over incomplete KGs. However, limited by their inherently shallow and static architectures, they can h…
GACT: Activation Compressed Training for Generic Network Architectures
Xiaoxuan Liu, Lianmin Zheng, Dequan Wang +9
Training large neural network (NN) models requires extensive memory resources, and Activation Compressed Training (ACT) is a promising approach to reduce training memory footprint.…
Rethinking the Setting of Semi-supervised Learning on Graphs
Ziang Li, Ming Ding, Weikai Li +4
We argue that the present setting of semisupervised learning on graphs may result in unfair comparisons, due to its potential risk of over-tuning hyper-parameters for models. In th…
GraphMAE: Self-Supervised Masked Graph Autoencoders
Zhenyu Hou, Xiao Liu, Yukuo Cen +4
Self-supervised learning (SSL) has been extensively explored in recent years. Particularly, generative SSL has seen emerging success in natural language processing and other AI fie…