- Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs
- Rethinking Node-wise Propagation for Large-scale Graph Learning
- Divide, Conquer, and Coalesce: Meta Parallel Graph Neural Network for IoT Intrusion Detection at Scale
- Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph
- EXGC: Bridging Efficiency and Explainability in Graph Condensation
- Fast Graph Condensation with Structure-based Neural Tangent Kernel
- λGrapher: A Resource-Efficient Serverless System for GNN Serving through Graph Sharing
- Cost-effective Data Labelling for Graph Neural Networks
- Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem
- Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach
- MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification
- A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification
- When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification
- Game-theoretic Counterfactual Explanation for Graph Neural Networks
- GNNShap: Scalable and Accurate GNN Explanation using Shapley Values
- Globally Interpretable Graph Learning via Distribution Matching
- Adversarial Mask Explainer for Graph Neural Networks
- Graph Fairness Learning under Distribution Shifts
- Fair Graph Representation Learning via Sensitive Attribute Disentanglement
- Endowing Pre-trained Graph Models with Provable Fairness
- Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation
- GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning
- Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search
- Can GNN be Good Adapter for LLMs?
- GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks
- MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs
- Inductive Graph Alignment Prompt: Bridging the Gap between Graph Pre-training and Inductive Fine-tuning From Spectral Perspective
- HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks
- GraphPro: Graph Pretraining and Prompt Learning for Recommendation
- Temporal Conformity-aware Hawkes Graph Network for Recommendations
- Linear-Time Graph Neural Networks for Scalable Recommendations
- Macro Graph Neural Networks for Online Billion-Scale Recommender Systems
- Distributionally Robust Graph-based Recommendation System
- Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning
- Hierarchical Graph Signal Processing for Collaborative Filtering
- General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
- DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning
- Self-Guided Robust Graph Structure Refinement
- GAUSS: GrAph-customized Universal Self-Supervised Learning
- VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation
- Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss
- Graph Contrastive Learning with Kernel Dependence Maximization for Social Recommendation
- Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving
- Disambiguated Node Classification with Graph Neural Networks
- Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks
- High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text Attributed Graphs
- Graph Contrastive Learning with Cohesive Subgraph Awareness
- Graph Contrastive Learning Reimagined: Exploring Universality
- Graph Contrastive Learning via Interventional View Generation
- Full-Attention Driven Graph Contrastive Learning: With Effective Mutual Information Insight
- MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
- Cooperative Classification and Rationalization for Graph Generalization
- Graph Out-of-Distribution Generalization via Causal Intervention
- DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy
- Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
- GNNFingers: A Fingerprinting Framework for Verifying Ownerships of Graph Neural Networks
- DenseFlow: Spotting Cryptocurrency Money Laundering in Ethereum Transaction Graphs
- Collaborative Metapath Enhanced Corporate Default Risk Assessment on Heterogeneous Graph
- Heterogeneous Subgraph Transformer for Fake News Detection
- Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets
- Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials
- Poisoning Attack on Federated Knowledge Graph Embedding
- ReliK: A Reliability Measure for Knowledge Graph Embeddings
- Using Model Calibration to Evaluate Link Prediction in Knowledge Graphs
- Unifying Local and Global Knowledge: Empowering Large Language Models as Political Experts with Knowledge Graphs
- SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding
- Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge Graph
- Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs
- A Method for Assessing Inference Patterns Captured by Embedding Models in Knowledge Graphs
- Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval
- HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding
- Bridging the Space Gap: Unifying Geometry Knowledge Graph Embedding with Optimal Transport
- UniLP: Unified Topology-aware Generative Framework for Link Prediction in Knowledge Graph
- Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning
- IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion
- Fact Embedding through Diffusion Model for Knowledge Graph Completion
- Hierarchical Position Embedding of Graphs with Landmarks and Clustering for Link Prediction
- Diffusion-based Negative Sampling on Graphs for Link Prediction
- Decoupled Variational Graph Autoencoder for Link Prediction
- Masked Graph Autoencoder with Non-discrete Bandwidths
- Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
- Dynamic Graph Information Bottleneck
- Memory Disagreement: A Pseudo-Labeling Measure from Training Dynamics for Semi-supervised Graph Learning
- On the Feasibility of Simple Transformer for Dynamic Graph Modeling
- TATKC: A Temporal Graph Neural Network for Fast Approximate Temporal Katz Centrality Ranking
- Efficient Exact and Approximate Betweenness Centrality Computation for Temporal Graphs
- Graph Anomaly Detection with Bi-level Optimization
- Friend or Foe? Mining Suspicious Behavior via Graph Capsule Infomax Detector against Fraudsters
- Extracting Small Subgraphs in Road Networks
- SMUG: Sand Mixing for Unobserved Class Detection in Graph Few-Shot Learning
- Invariant Graph Learning for Causal Effect Estimation
- Identifying VPN Servers through Graph-Represented Behaviors
- Calibrating Graph Neural Networks from a Data-centric Perspective
- Graph Principal Flow Network for Conditional Graph Generation
- A Quasi-Wasserstein Loss for Learning Graph Neural Networks
- ARTEMIS: Detecting Airdrop Hunters in NFT Markets with a Graph Learning System
- Diagrammatic Reasoning for ALC Visualization with Logic Graphs
- GAMMA: Graph Neural Network-Based Multi-Bottleneck Localization for Microservices Applications