3 citations · 10 across the 4 of their papers we have counts for
4 papers
Exploring the Potential of Large Language Models in Graph Generation
Yang Yao, Xin Wang, Zeyang Zhang +6
Large language models (LLMs) have achieved great success in many fields, and recent works have studied exploring LLMs for graph discriminative tasks such as node classification. Ho…
Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision
Zeyang Zhang, Xin Wang, Ziwei Zhang +3
The existing graph neural architecture search (GNAS) methods heavily rely on supervised labels during the search process, failing to handle ubiquitous scenarios where supervisions…
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
Zeyang Zhang, Xin Wang, Ziwei Zhang +5
Dynamic graph neural networks (DyGNNs) currently struggle with handling distribution shifts that are inherent in dynamic graphs. Existing work on DyGNNs with out-of-distribution se…
Graph Meets LLMs: Towards Large Graph Models
Ziwei Zhang, Haoyang Li, Zeyang Zhang +3
Large models have emerged as the most recent groundbreaking achievements in artificial intelligence, and particularly machine learning. However, when it comes to graphs, large mode…