SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detection

SAHG detects LLM-driven social bots by applying direction-dependent hyperbolic curvature and dual-channel feature fusion, achieving top accuracy and F1 across three benchmarks.

Hanning Lu, Yingguang Yang, Jinwei Su, Yang; Liu and 7 more

Published May 28, 2026 · 0 citations

Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning

FedVN uses learnable virtual nodes and client-specific edge generators to eliminate graph distribution shifts across federated clients, improving GNN performance.

Xingbo Fu, Zihan Chen, Yinhan He, Song Wang and 3 more

Published Apr 11, 2025 · 3 citations

Out-of-Distribution Generalization on Graphs via Progressive Inference

GPro improves graph out-of-distribution generalization by decomposing causal invariant learning into progressive inference steps and augmenting training with counterfactual samples, outperforming state-of-the-art methods by 4.91%.

Yiming Xu, Bin Shi, Zhen Peng, Huixiang Liu and 2 more

Published Apr 11, 2025 · 3 citations

BrainMAP: Learning Multiple Activation Pathways in Brain Networks

BrainMAP learns multiple brain network activation pathways via sequential models and Mixture-of-Experts, improving fMRI analysis and interpretability.

Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding and 7 more

Published Apr 11, 2025 · 2 citations

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization

Proposed framework improves graph OOD generalization by jointly enhancing environment augmentation and invariant subgraph extraction consistency.

Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen and 3 more

Published Jan 7, 2025 · 0 citations

Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective

A spectral benchmark reveals that graph neural networks capture diverse frequency components through non-linear layers, not just neighborhood aggregation filters.

Yushun Dong, Patrick Soga, Yinhan He, Song Wang and 1 more

Published Dec 10, 2024 · 1 citation

Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization

A modifier unifies graph augmentation and invariant subgraph extraction to improve distribution and label consistency for graph OOD generalization.

Song Wang, Xiaodong Yang, Rashidul Islam, Huiyuan Chen and 3 more

Published Dec 9, 2024 · 3 citations

Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning

Causal attention learning via backdoor adjustment separates causal and shortcut graph features to improve out-of-distribution generalization of GNNs.

Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang and 3 more

Published Feb 6, 2024 · 31 citations

HOFA: Twitter Bot Detection with Homophily-Oriented Augmentation and Frequency Adaptive Attention

HOFA improves Twitter bot detection via homophily-oriented graph augmentation and frequency-adaptive attention, achieving state-of-the-art results on three benchmarks.

Sen Ye, Zhaoxuan Tan, Zhenyu Lei, He, Ruijie and 3 more

Published Jun 22, 2023 · 3 citations

Over-Sampling Strategy in Feature Space for Graphs based Class-imbalanced Bot Detection

OS-GNN generates minority-class feature-space samples via neighborhood aggregation for graph-based bot detection, outperforming baselines without edge synthesis.

Shuhao Shi, Kai Qiao, Jie Chi Yang, Baojie Song and 2 more

Published Feb 14, 2023 · 2 citations

TwiBot-22: Towards Graph-Based Twitter Bot Detection

TwiBot-22 introduces the largest graph-based Twitter bot benchmark with high-quality annotations and evaluates 35 baselines across nine datasets.

Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang and 18 more

Published Jun 9, 2022 · 46 citations · Code ★ 270

Adaptive Attribute Completion with Representation Space for Incomplete Graph Domain Adaptation

Niya Yang, Di Jin, Zhizhi Yu, Liang Yang and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

Fast Algorithms for the Label Propagation Operator on Signed Graphs

Yubo Sun, Zhongzhi Zhang

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

gHAWK: Structural Encoding for Scalable Training of Graph Neural Networks on Knowledge Graphs

Humera Sabir, Fatima Farooq, Ashraf Aboulnaga

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

Propagate to Discover: Graph-Structured Propagation for Generalized Category Discovery

yongqi tian, Junyong Liu, Jinkun Ran, Haoyuan He and 1 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

Learning Pseudo-Riemannian Manifolds for Heterophilic Graphs via Graph Signature

Yun Young Choi, Asung Kil, Sun Woo Park, Minho Lee and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Understanding Graph Self-Supervised Pre-training under Distribution Shifts: A Scaling Law Perspective

Bingheng Li, Shikun Liu, Yu Song, Jay Revolinsky and 4 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

S&P: Towards Scalable and Powerful Graph Learning with Hierarchical Structural Acquisition

Mingqi Yang, Zhaoyu Liu, Wenjie Feng

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

A2I: Adjacency-to-Image Structural Encodings for Graph Learning

Heesoo Jung, Hogun Park

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

Traffic STGNNs across Sensor, City, and Time Shifts: Routing Concentration Tracks Sensitivity to Sensor Dropout

XiLe Wang, Mingqi Yang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026