"node classification" Papers
53 papers found • Page 1 of 2
Conference
$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
Xiaojun Guo, Ang Li, Yifei Wang et al.
Attack by Yourself: Effective and Unnoticeable Multi-Category Graph Backdoor Attacks with Subgraph Triggers Pool
Jiangtong Li, Dongyi Liu, Kun Zhu et al.
Bonsai: Gradient-free Graph Condensation for Node Classification
Mridul Gupta, Samyak Jain, Vansh Ramani et al.
Centrality-guided Pre-training for Graph
Bin Liang, Shiwei Chen, Lin Gui et al.
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Lequan Lin, Dai Shi, Andi Han et al.
DUALFormer: Dual Graph Transformer
Zhuo Jiaming, Yuwei Liu, Yintong Lu et al.
Equivariance Everywhere All At Once: A Recipe for Graph Foundation Models
Ben Finkelshtein, Ismail Ilkan Ceylan, Michael Bronstein et al.
Exact Certification of (Graph) Neural Networks Against Label Poisoning
Mahalakshmi Sabanayagam, Lukas Gosch, Stephan Günnemann et al.
Fully-inductive Node Classification on Arbitrary Graphs
Jianan Zhao, Zhaocheng Zhu, Mikhail Galkin et al.
GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
Shengbo Gong, Juntong Ni, Noveen Sachdeva et al.
GD$^2$: Robust Graph Learning under Label Noise via Dual-View Prediction Discrepancy
Kailai Li, Jiong Lou, Jiawei Sun et al.
Generative Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi Ma et al.
GnnXemplar: Exemplars to Explanations - Natural Language Rules for Global GNN Interpretability
Burouj Armgaan, Eshan Jain, Harsh Pandey et al.
GRAVER: Generative Graph Vocabularies for Robust Graph Foundation Models Fine-tuning
Haonan Yuan, Qingyun Sun, Junhua Shi et al.
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending Against Poisoning Attacks
Ao Liu, Wenshan Li, Beibei Li et al.
GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers
GUOGUO AI, Guansong Pang, Hezhe Qiao et al.
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
Shenzhi Yang, Junbo Zhao, Sharon Li et al.
How Particle System Theory Enhances Hypergraph Message Passing
Yixuan Ma, Kai Yi, Pietro Lió et al.
Improving Graph Neural Networks by Learning Continuous Edge Directions
Seong Ho Pahng, Sahand Hormoz
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
Memorization in Graph Neural Networks
Adarsh Jamadandi, Jing Xu, Adam Dziedzic et al.
Node-Time Conditional Prompt Learning in Dynamic Graphs
Xingtong Yu, Zhenghao Liu, Xinming Zhang et al.
Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment
Xiao Shen, Zhihao Chen, Shirui Pan et al.
Preference-driven Knowledge Distillation for Few-shot Node Classification
Xing Wei, Chunchun Chen, Rui Fan et al.
Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
Feng Ji, Yanan Zhao, KAI ZHAO et al.
Rethinking Tokenized Graph Transformers for Node Classification
Jinsong Chen, Chenyang Li, Gaichao Li et al.
Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum
Haoyang Li, Xin Wang, Zeyang Zhang et al.
Spectro-Riemannian Graph Neural Networks
Karish Grover, Haiyang Yu, Xiang song et al.
Taxonomy of reduction matrices for Graph Coarsening
Antonin Joly, Nicolas Keriven, Aline Roumy
Tokenphormer: Structure-aware Multi-token Graph Transformer for Node Classification
Zijie Zhou, Zhaoqi Lu, Xuekai Wei et al.
Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models
Siwei Zhang, Yun Xiong, Yateng Tang et al.
UniGTE: Unified Graph–Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains
Duo Wang, Yuan Zuo, Guangyue Lu et al.
Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors
Jinhyeok Choi, Heehyeon Kim, Joyce Jiyoung Whang
Amortized Variational Deep Kernel Learning
Alan Matias, César Lincoln Mattos, Joao Paulo Gomes et al.
Class-Imbalanced Graph Learning without Class Rebalancing
Zhining Liu, Ruizhong Qiu, Zhichen Zeng et al.
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-Smoothness in Deep GNNs
Jin Li, Qirong Zhang, Shuling Xu et al.
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
Soo Yong Lee, Sunwoo Kim, Fanchen Bu et al.
GATE: How to Keep Out Intrusive Neighbors
Nimrah Mustafa, Rebekka Burkholz
Graph Attention Retrospective
Kimon Fountoulakis, Amit Levi, Shenghao Yang et al.
Graph Contrastive Invariant Learning from the Causal Perspective
9672 Yanhu Mo, Xiao Wang, Shaohua Fan et al.
Graph Neural Networks with a Distribution of Parametrized Graphs
See Hian Lee, Feng Ji, Kelin Xia et al.
Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification
Xixun Lin, Wenxiao Zhang, Fengzhao Shi et al.
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Kangkang Lu, Yanhua Yu, Hao Fei et al.
Mitigating Label Noise on Graphs via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia et al.
Pairwise Alignment Improves Graph Domain Adaptation
Shikun Liu, Deyu Zou, Han Zhao et al.
PC-Conv: Unifying Homophily and Heterophily with Two-Fold Filtering
Bingheng Li, Erlin Pan, Zhao Kang
Poincaré Differential Privacy for Hierarchy-Aware Graph Embedding
Yuecen Wei, Haonan Yuan, Xingcheng Fu et al.
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
Rui Miao, Kaixiong Zhou, Yili Wang et al.
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.