14 citations · 54 across the 12 of their papers we have counts for
5 papers · 1 filter
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao +4
Graph Neural Networks (GNNs) have shown great promise in learning node embeddings for link prediction (LP). While numerous studies aim to improve the overall LP performance of GNNs…
A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications
Yi Zhang, Yuying Zhao, Zhaoqing Li +5
Graph Neural Networks (GNNs) have gained significant attention owing to their ability to handle graph-structured data and the improvement in practical applications. However, many o…
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan A. Rossi +3
The `pre-train, prompt, predict' paradigm of large language models (LLMs) has achieved remarkable success in open-domain question answering (OD-QA). However, few works explore this…
Fairness-Aware Graph Neural Networks: A Survey
April Chen, Ryan A. Rossi, Namyong Park +6
Graph Neural Networks (GNNs) have become increasingly important due to their representational power and state-of-the-art predictive performance on many fundamental learning tasks.…
Fairness and Diversity in Recommender Systems: A Survey
Yuying Zhao, Yu Wang, Yunchao Liu +3
Recommender systems are effective tools for mitigating information overload and have seen extensive applications across various domains. However, the single focus on utility goals…