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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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NeurIPS 2026SpotlightYantaiGraph neural networks

RAMA: Resistance-Aware Multi-Hop Aggregation Graph Representation Learning for Robust Ethereum Account Classification

Zhaowei Liu, zengyang zhang, HaitaoYang, Yao Shan and 2 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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IncAgg: Efficient Memory-Enhanced Graph Learning via Incremental Aggregation

Xingyue Shi, Zhichao Hou, Jiahao Zhang, Suhang Wang and 3 more

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

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OHATP: Graph Anomaly Detection with Orthogonal-Hyperspherical Augmentation and Topology Perception

yihang qiu, Yi Zhang, Di Xiong, Ge Gao and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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$\texttt{bispectrum}$: Selective $G$-Bispectra Made Practical

Johan Mathe, Adele Lantow, Simon Mataigne, Nina Miolane

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

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Hierarchical Graph Representation Learning with Pooling-Induced Substructures

Luca Sbicego, Xiaowen Dong, Dorina Thanou

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

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Mitigating Over-squashing without Rewiring: A Sheaf Effective Resistance Perspective

André Ribeiro Guimarães, Germano Barcelos, Amauri Souza, Diego Mesquita and 1 more

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

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SGNNBench: A Holistic Evaluation of Spiking Graph Neural Networks on Large-scale Graphs

Huizhe Zhang, Jintang Li, Yuchang Zhu, Huazhen Zhong and 1 more

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

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Transductive Generalization for GNNs via Optimal Transport

MoonJeong Park, Seungbeom Lee, Kyungmin Kim, Jaeseung Heo and 4 more

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

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Online Learning with Certified Unlearning over Graphs

Ruijie Du, Yanning Shen

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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When Edge Independence Fails: Joint Graph Diffusion with Latent Sociability Priors

Adarsh Jamadandi, Nicolas Keriven, Aline Roumy

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

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PATH: A Dual Perspective for High-quality Text-attributed Graph Learning

Yuhang Pei, Fanchun Meng, Changhu Wang, Tao Ren and 5 more

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

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CLEAR: Complementary Tripartite Play with Bayesian Calibration for Semi-Supervised Edge Classification

Zhipeng Sun, Fanchun Meng, Jiazhen Huang, Yongpeng Zhang and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Implicit Neural Representations for Variational Problems on Graphons

Taeyoung Kim, Jineon Baek, Joonkyung Lee, Hongseok Yang

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

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Network Intervention by Polling Strategic Agents

Chenyu Zhang, Rohit Parasnis, Saurabh Amin

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

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Orlicz–Sobolev with Musielak: An Efficient Regularization Approach for Graph-based IPM

Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Neutral-atom quantum features as complementary structural encodings for graph learning

Igor Sokolov, Mathieu Garrigues, Matthias Hecker, Lorenzo Moro and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Releasing Anchors from Cross-View Correspondence: Probabilistic Multi-View Anchor Graph Clustering

Zhoumin Lu, Yongbo Yu, Yu Duan, Feiping Nie and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Robust and Hard-to-Remove GNN Watermarking via Topological Invariant Perception

JIPENG LI, Yanning Shen

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

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Graph and Simplicial Complex Prediction Gaussian Process via Hodgelet Representations

Mathieu Alain, So Takao, Bastian Rieck, Xiaowen Dong and 1 more

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

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Stage-Aware Dual Alignment for Covariate Shift in Graph Domain Adaptation

Hongwei Wen, Can Zhang, Haoyu He, Xintao Zhao and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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FedCAG: Federated Causality-Aware Graph Learning for Multi-Cloud Workload Forecasting

Yongcan Luo, Zhengjie Yang, Jiahao Zheng, Hao Wang and 2 more

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

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Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs

Zhewei Chen, Hao Zhu, Jiaojiao Jiang, Ahad N. Zehmakan

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

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EnerGNN: Learning Optimization-Compatible Energy Functions for Exact Constrained Combinatorial Inference

Niki Triantafyllou, Maria Papathanasiou

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

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Reasoning over Coupled Receptive Fields: Eliminating Subgraph Redundancy at Scale

Jing Yang, Bo Wen, Yuan Gao, XiaowenJiang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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GEM: A Dual-Scale Architecture for Graph-Level Hierarchical Representation Learning

Zhaowei Wu, Kaizhong Zheng, Guangmingzi Yang, Shuai Jiang and 2 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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Caterpillar GNN: Replacing Message Passing with Graph-Level Aggregation

Marek Černý

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Learning Transferable Representations from Operating System Entities via Provenance Graph Distillation

Tristan Bilot, Xueyuan Han, Thomas Pasquier

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

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SAG-Sep: Sparse Augmented Graphs and Onion-Guided Search for Rounded Capacity Cut Separation

Haoran Liu, Guanyi Wang, Yu Yang

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Adaptive Feature Propagation for Attribute-Missing Graph Clustering

Xiang Long, QIANQIAN WANG

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Revisiting Autoregressive GCNs for Vehicle Routing Problems

Zhipeng Zhong, Junquan Huang, Yu Huang, Boyuan Zheng and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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How Hard Is It for Message-Passing GNNs to Simulate One Weisfeiler-Lehman Color-Refinement Step?

Guanyu Cui, Yuhe Guo, Zhewei Wei, Hsin-Hao Su

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Fiedler-Regularized Causal Discovery for Sparse Connected DAGs

Amine M'Charrak, Abbavaram Gowtham Reddy, Thomas Lukasiewicz, Michael Bronstein and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Heterogeneous Graph Federated Learning with Structure-Aware Data-Free Distillation

Lili Guo, Qi Li, Ruoyu Wang, Chao Li and 1 more

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

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Bias, Measurement Error, and Double-Dipping: When Can GNN Convolutions Help Brain Connectome Prediction?

Tommaso Castellani, Jiaqi Li, Muriah D Wheelock, Rezwana R Razzaque and 3 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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Dynamic Spectral Federated Graph-Level Clustering

Wenxin Zhang, Xi Xuan, Guangzhen Yao, Feng Zhou and 6 more

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

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Module-Aware Optimization for Graph Neural Networks

Guy Hadad, Haggai Roitman, Moshe Eliasof, Bracha Shapira

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Benchmarking Graph Self-Supervised Learning for Node-Level Tasks: Insights and Strong Baseline

Dmitry Eremeev, Gleb Bazhenov, Oleg Platonov, Artem Babenko and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Matrix-Free Stochastic Training of Low-Rank Spectral Graph Learning via Randomized Adaptive Spectral Estimation

Mingqi Yang, Yanming Shen

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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MIRAGE: Hierarchical MI-Surrogate Regulation for Graph Contrastive Learning

Qi Teng, Xueer Wang

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

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Beyond Node Sequences: Relational Diffusion for Unified Graph Learning

Xianan Wang, Wenji Hu, Chunyu Wei, Yueguo Chen

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

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