Xingcheng Fu

26 papers · 2022–2026 · 6 conferences · across top CS/AI conferences

Achievements

+10 more ↓

🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🌈 Renaissance Researcher (9)

🧭 Keyword Pioneer 🤝 Dynamic Duo (19) 🏆 Keyword Champion (2) 🏆 Grand Slam 🔬 Deep Specialist (18) 🔥 Unstoppable (5) ⚡ Prolific Year (13) 🗃️ Keyword Collector (108) ❓ The Questioner (2) 💎 Century Club (21)

Conferences

AAAI (14) IJCAI (4) NIPS (3) ICLR (2) ICML (2) CVPR (1)

Top co-authors

Qingyun Sun (24) Jianxin Li (18) Haonan Yuan (11) Hao Peng (9) Cheng Ji (8) Yisen Gao (7) Xianxian Li (7) Yuecen Wei (7) Beining Yang (5) Philip S. Yu (4)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

graph neural network (14) graph representation learning (4) representation learning (4) node classification (4) information bottleneck (4) privacy leakage (3) graph structure learning (3) message passing (3) hyperbolic space (2) variational inference (2) graph contrastive learning (2) contrastive learning (2) node representation (2) variational information bottleneck (2) dynamic graph (2) information theory (2) mutual information (2) self-supervised learning (2) adversarial robustness (2) mixture of expert (2)

Papers

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space AAAI 2026 Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models AAAI 2026 Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning AAAI 2026 SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation AAAI 2026 Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks AAAI 2026 IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning ICLR 2025 DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models AAAI 2025 Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding CVPR 2025 ST-GCond: Self-supervised and Transferable Graph Dataset Condensation ICLR 2025 How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees ICML 2025 OS-GCL: A One-Shot Learner in Graph Contrastive Learning IJCAI 2025 Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning IJCAI 2025 An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks IJCAI 2025 Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks IJCAI 2025 GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts AAAI 2025 Prompt-based Unifying Inference Attack on Graph Neural Networks AAAI 2025 Discrete Curvature Graph Information Bottleneck AAAI 2025 Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck AAAI 2025 Hyperbolic Geometric Latent Diffusion Model for Graph Generation ICML 2024 Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding AAAI 2024 GC-Bench: An Open and Unified Benchmark for Graph Condensation NIPS 2024 ReGCL: Rethinking Message Passing in Graph Contrastive Learning AAAI 2024 Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization NIPS 2023 Does Graph Distillation See Like Vision Dataset Counterpart? NIPS 2023 Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information AAAI 2023 Graph Structure Learning with Variational Information Bottleneck AAAI 2022