30 citations · 31 across the 7 of their papers we have counts for
5 papers · 1 filter
CORE: Contrastive Masked Feature Reconstruction on Graphs
Jianyuan Bo, Yuan Fang
In the rapidly evolving field of self-supervised learning on graphs, generative and contrastive methodologies have emerged as two dominant approaches. Our study focuses on masked f…
A Probabilistic Framework for Temporal Distribution Generalization in Industry-Scale Recommender Systems
Yuxuan Zhu, Cong Fu, Yabo Ni +2
Temporal distribution shift (TDS) erodes the long-term accuracy of recommender systems, yet industrial practice still relies on periodic incremental training, which struggles to ca…
Contrastive General Graph Matching with Adaptive Augmentation Sampling
Jianyuan Bo, Yuan Fang
Graph matching has important applications in pattern recognition and beyond. Current approaches predominantly adopt supervised learning, demanding extensive labeled data which can…
Diffusion-based Negative Sampling on Graphs for Link Prediction
Trung-Kien Nguyen, Yuan Fang
Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link…
Graph Foundation Models: Concepts, Opportunities and Challenges
Jiawei Liu, Cheng Yang, Zhiyuan Lu +8
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and seve…