"message passing" Papers
16 papers found
Conference
Accurate and Scalable Graph Neural Networks via Message Invariance
Zhihao Shi, Jie Wang, Zhiwei Zhuang et al.
ICLR 2025arXiv:2502.19693
3
citations
Bundle Neural Network for message diffusion on graphs
Jacob Bamberger, Federico Barbero, Xiaowen Dong et al.
ICLR 2025arXiv:2405.15540
8
citations
DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion
Jin Li, Zezhong Ding, Xike Xie
NEURIPS 2025arXiv:2507.11229
1
citations
Learning Long Range Dependencies on Graphs via Random Walks
Dexiong Chen, Till Schulz, Karsten Borgwardt
ICLR 2025arXiv:2406.03386
20
citations
Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective
Ming Gu, Zhuonan Zheng, Sheng Zhou et al.
NEURIPS 2025arXiv:2412.09805
3
citations
Normalize Then Propagate: Efficient Homophilous Regularization for Few-Shot Semi-Supervised Node Classification
Baoming Zhang, MingCai Chen, Jianqing Song et al.
AAAI 2025paperarXiv:2501.08581
1
citations
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade et al.
ICLR 2025arXiv:2407.01214
8
citations
The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited
Floriano Tori, Vincent Holst, Vincent Ginis
ICLR 2025arXiv:2407.09381
8
citations
Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling
Xinyue Fang, Zhen Huang, Zhiliang Tian et al.
AAAI 2025paperarXiv:2409.11283
6
citations
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs
Teng Xiao, Huaisheng Zhu, Zhiwei Zhang et al.
ICML 2024
Heterogeneous Graph Learning for Scene Graph Prediction in 3D Point Clouds
Yanni Ma, Hao Liu, Yun Pei et al.
ECCV 2024
3
citations
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
ICML 2024oralarXiv:2406.02740
28
citations
Multi-Track Message Passing: Tackling Oversmoothing and Oversquashing in Graph Learning via Preventing Heterophily Mixing
Hongbin Pei, Yu Li, Huiqi Deng et al.
ICML 2024spotlight
Provably Powerful Graph Neural Networks for Directed Multigraphs
Beni Egressy, Luc von Niederhäusern, Jovan Blanuša et al.
AAAI 2024paperarXiv:2306.11586
33
citations
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
ICML 2024arXiv:2312.01538
13
citations
Towards Inductive Robustness: Distilling and Fostering Wave-Induced Resonance in Transductive GCNs against Graph Adversarial Attacks
Ao Liu, Wenshan Li, Tao Li et al.
AAAI 2024paperarXiv:2312.08651
7
citations