Xingcheng Fu

Affiliations

Guangxi Normal University

papers

209

total citations

papers (15)

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

AAAI 2025arXiv

citations

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

AAAI 2025arXiv

citations

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding

AAAI 2024arXiv

citations

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

ICML 2025

citations

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

AAAI 2025arXiv

citations

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

ICLR 2025arXiv

citations

Prompt-based Unifying Inference Attack on Graph Neural Networks

AAAI 2025arXiv

citations

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

NEURIPS 2025arXiv

citations

Discrete Curvature Graph Information Bottleneck

AAAI 2025arXiv

citations

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

CVPR 2025arXiv

citations

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

NEURIPS 2025arXiv

citations

Xingcheng Fu

Affiliations

papers (15)

Does Graph Distillation See Like Vision Dataset Counterpart?

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

Hyperbolic Geometric Latent Diffusion Model for Graph Generation

ReGCL: Rethinking Message Passing in Graph Contrastive Learning

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

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

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding

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

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

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

Prompt-based Unifying Inference Attack on Graph Neural Networks

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

Discrete Curvature Graph Information Bottleneck

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

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

papers (15)

Does Graph Distillation See Like Vision Dataset Counterpart?

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

Hyperbolic Geometric Latent Diffusion Model for Graph Generation

ReGCL: Rethinking Message Passing in Graph Contrastive Learning

GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts

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

Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding

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

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

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

Prompt-based Unifying Inference Attack on Graph Neural Networks

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

Discrete Curvature Graph Information Bottleneck

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

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