Xingcheng Fu

Orcid: 0000-0002-4643-8126

According to our database¹, Xingcheng Fu authored at least 65 papers between 2019 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

Evolving Graph Learning for Out-of-Distribution Generalization in Non-Stationary Environments.

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[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., March, 2026

Retrieving Minimal and Sufficient Reasoning Subgraphs with Graph Foundation Models for Path-aware GraphRAG.

[BibT_eX]

[DOI]

CoRR, March, 2026

Zero-shot Generalizable Graph Anomaly Detection with Mixture of Riemannian Experts.

[BibT_eX]

[DOI]

CoRR, February, 2026

Rethinking heterophilic graph learning via graph curvature.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2026

RAG-GFM: Overcoming In-Memory Bottlenecks in Graph Foundation Models via Retrieval-Augmented Generation.

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[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Towards Geometry-Consistent Federated Graph Learning.

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[DOI]

Proceedings of the ACM Web Conference 2026, 2026

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model.

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Proceedings of the ACM Web Conference 2026, 2026

Graph Diffusion Evolution Model for Multi-Conditional Molecular Generation.

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Proceedings of the ACM Web Conference 2026, 2026

Mitigating Privacy Risks in Graph Condensation from a Hyperbolic Geometry Perspective.

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Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation.

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[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks.

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Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Towards Effective, Stealthy, and Persistent Backdoor Attacks Targeting Graph Foundation Models.

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[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning.

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[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Towards LLM-Empowered Knowledge Tracing via LLM-Student Hierarchical Behavior Alignment in Hyperbolic Space.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

SA<sup>2</sup>GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation.

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[DOI]

CoRR, December, 2025

User preference representation and dual contrastive learning for knowledge-aware recommendation.

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[DOI]

Int. J. Mach. Learn. Cybern., November, 2025

GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning.

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[DOI]

CoRR, November, 2025

GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation.

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CoRR, November, 2025

Robust Graph Condensation via Classification Complexity Mitigation.

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CoRR, October, 2025

Toward a Unified Geometry Understanding: Riemannian Diffusion Framework for Graph Generation and Prediction.

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CoRR, October, 2025

SDA-PLANNER: State-Dependency Aware Adaptive Planner for Embodied Task Planning.

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CoRR, September, 2025

A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models.

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[DOI]

Int. J. Mach. Learn. Cybern., August, 2025

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning.

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[DOI]

CoRR, July, 2025

Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning.

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[DOI]

CoRR, July, 2025

Controllable Logical Hypothesis Generation for Abductive Reasoning in Knowledge Graphs.

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CoRR, May, 2025

Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification.

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[DOI]

Proceedings of the ACM on Web Conference 2025, 2025

Graph Size-imbalanced Learning with Energy-guided Structural Smoothing.

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[DOI]

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks.

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[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks.

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[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Mitigating Message Imbalance in Fraud Detection with Dual-View Graph Representation Learning.

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[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

OS-GCL: A One-Shot Learner in Graph Contrastive Learning.

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[DOI]

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees.

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Proceedings of the Forty-second International Conference on Machine Learning, 2025

ST-GCond: Self-supervised and Transferable Graph Dataset Condensation.

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[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

IGL-Bench: Establishing the Comprehensive Benchmark for Imbalanced Graph Learning.

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[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SIGMA: A Dual-Agent Reinforcement Learning-OptimizedFramework for Graph Classification.

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[DOI]

Proceedings of the 2025 7th International Conference on Distributed Artificial Intelligence, 2025

Galaxy Walker: Geometry-aware VLMs For Galaxy-scale Understanding.

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[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Frontiers in Graph Machine Learning for the Large Model Era.

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[DOI]

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models.

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[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Prompt-based Unifying Inference Attack on Graph Neural Networks.

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[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Discrete Curvature Graph Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck.

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[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

CausalFD: causal invariance-based fraud detection against camouflaged preference.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., November, 2024

Dynamic Graph Information Bottleneck.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

GC-Bench: An Open and Unified Benchmark for Graph Condensation.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Hyperbolic Geometric Latent Diffusion Model for Graph Generation.

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[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

ReGCL: Rethinking Message Passing in Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Robust and Generalized Framework for Adversarial Graph Embedding.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., November, 2023

Higher-order memory guided temporal random walk for dynamic heterogeneous network embedding.

[BibT_eX]

[DOI]

Pattern Recognit., November, 2023

Heterogeneous graph neural network with semantic-aware differential privacy guarantees.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., October, 2023

Adaptive curvature exploration geometric graph neural network.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., May, 2023

AIC-GNN: Adversarial information completion for graph neural networks.

[BibT_eX]

[DOI]

Inf. Sci., May, 2023

Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification.

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[DOI]

Proceedings of the ACM Web Conference 2023, 2023

Unbiased and Efficient Self-Supervised Incremental Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Does Graph Distillation See Like Vision Dataset Counterpart?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

POINE<sup>2</sup>: Improving Poincaré Embeddings for Hierarchy-Aware Complex Query Reasoning over Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Self-Organization Preserved Graph Structure Learning with Principle of Relevant Information.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Curvature Graph Generative Adversarial Networks.

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[DOI]

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2022

Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Graph Structure Learning with Variational Information Bottleneck.

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[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2021

2019

A three-phase approach to differentially private crucial patterns mining over data streams.

[BibT_eX]

[DOI]

Comput. Secur., 2019

Xingcheng Fu

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