Submissions in WSDM 2025

Limited Supervision

Training MLPs on Graphs without Supervision
Inductive Graph Few-shot Class Incremental Learning

Link Prediction

Hyperdimensional Representation Learning for Node Classification and Link Prediction
Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs

Language Models

LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework
MoKGNN: Boosting Graph Neural Networks via Mixture of Generic and Task-Specific Language Models
UniGLM: Training One Unified Language Model for Text-Attributed Graphs Embedding

Dynamic Graphs

Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding
Hawkes Point Process-Enhanced Dynamic Graph Neural Networks

Multigraphs

Prospective Multi-Graph Cohesion for Multivariate Time Series Anomaly Detection
Polaris: Sampling from the Multigraph Configuration Model with Prescribed Color Assortativity

Knowledge Graphs

Adaptive Graph Enhancement for Imbalanced Multi-relation Graph Learning
Neo-TKGC: Enhancing Temporal Knowledge Graph Completion with Integrated Node Weights and Future Information

Heterogeneous Graphs

HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning
Heterogeneous Graph Diffusion Model

Hypergraphs

Self-supervised Time-aware Heterogeneous Hypergraph Learning for Dynamic Graph-level Classification
An aspect performance-aware hypergraph neural network for review-based recommendation

Recommendation

Simple Graph Neural Networks for Recommendation
Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multi-modal Recommendation

Causality

Heterophilic Graph Neural Networks Optimization with Causal Message-passing
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data

Imbalanced Data

Edge Classification on Graphs: New Directions in Topological Imbalance
Graph Size-imbalanced Learning with Energy-guided Structural Smoothing

Miscellaneous

Beyond Message-Passing: Generalization of Graph Neural Networks via Feature Perturbation
FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning
Q-DISCO: Query-Centric Densest Subgraphs in Networks with Opinion Information
Robustness Verification of Deep Graph Neural Networks Tightened by Linear Approximation
CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders
RSM: Reinforced Subgraph Matching Framework with Fine-grained Operation based Search Plan
Improving CTR Prediction with Graph-Enhanced Interest Networks for Sparse Behavior Sequences
D$^2$: Customizing Two-Stage Graph Neural Networks for Early Rumor Detection through Cascade Diffusion Prediction