Xingcheng Fu
26 papers · 2022–2026 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
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Deep Learning
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Learning Types · Machine Learning
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Keywords
graph neural network
(15)
node classification
(5)
information bottleneck
(4)
graph representation learning
(4)
representation learning
(4)
mixture of expert
(3)
privacy leakage
(3)
graph foundation model
(3)
self-supervised learning
(3)
mutual information
(3)
message passing
(3)
graph structure learning
(3)
contrastive learning
(2)
variational inference
(2)
node representation
(2)
hyperbolic space
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dynamic graph
(2)
adversarial robustness
(2)
variational information bottleneck
(2)
graph classification
(2)
Papers
Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning
AAAI 2026
Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks
AAAI 2026
SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation
AAAI 2026
Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models
AAAI 2026
Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space
AAAI 2026
An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks
IJCAI 2025
Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck
AAAI 2025
DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models
AAAI 2025
Discrete Curvature Graph Information Bottleneck
AAAI 2025
Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding
CVPR 2025
GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts
AAAI 2025
How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees
ICML 2025
IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning
ICLR 2025
Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks
IJCAI 2025
Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning
IJCAI 2025
OS-GCL: A One-Shot Learner in Graph Contrastive Learning
IJCAI 2025
Prompt-based Unifying Inference Attack on Graph Neural Networks
AAAI 2025
ST-GCond: Self-supervised and Transferable Graph Dataset Condensation
ICLR 2025
GC-Bench: An Open and Unified Benchmark for Graph Condensation
NeurIPS 2024
Hyperbolic Geometric Latent Diffusion Model for Graph Generation
ICML 2024
Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
AAAI 2024
ReGCL: Rethinking Message Passing in Graph Contrastive Learning
AAAI 2024
Does Graph Distillation See Like Vision Dataset Counterpart?
NeurIPS 2023
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization
NeurIPS 2023
Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information
AAAI 2023
Graph Structure Learning with Variational Information Bottleneck
AAAI 2022