59 citations · 180 across the 28 of their papers we have counts for
28 papers
OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction
Xin Wang, Linxin Xiao, Yang Yao +1
Drug synergy prediction (DSP) aims to identify efficacious drug combinations under various cellular contexts with different targets. However, the continual emergence of novel compo…
A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning
Haibo Chen, Xin Wang, Jiaheng Chao +2
Leveraging Graph Neural Networks (GNNs) as graph encoders and aligning the resulting representations with Large Language Models (LLMs) through alignment instruction tuning has beco…
Asymmetric Generative Recommendation via Kronecker Residual Bridge and Multi-Faceted Hierarchical Quantization
Bin Huang, Xin Wang, Junwei Pan +6
Generative Recommendation (GenRec) models reformulate recommendation as a sequence generation task, representing items as discrete Semantic IDs used symmetrically as both inputs an…
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…