Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models
Fuente:
arXiv
Saved in:
| Main Authors: | Ma, Zhongtian, Zhang, Qiaosheng, Zhou, Bocheng, Zhang, Yexin, Hu, Shuyue, Wang, Zhen |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Gated Graph Attention Networks with Learnable Temperature
by: Ma, Zhongtian, et al.
Published: (2026)
by: Ma, Zhongtian, et al.
Published: (2026)
Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability
by: Zhang, Yexin, et al.
Published: (2026)
by: Zhang, Yexin, et al.
Published: (2026)
Community Detection in the Multi-View Stochastic Block Model
by: Zhang, Yexin, et al.
Published: (2024)
by: Zhang, Yexin, et al.
Published: (2024)
Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms
by: Ma, Zhongtian, et al.
Published: (2024)
by: Ma, Zhongtian, et al.
Published: (2024)
Is Graph Convolution Always Beneficial For Every Feature?
by: Zheng, Yilun, et al.
Published: (2024)
by: Zheng, Yilun, et al.
Published: (2024)
Community Detection for Contextual-LSBM: Theoretical Limitations of Misclassification Rate and Efficient Algorithms
by: Jin, Dian, et al.
Published: (2025)
by: Jin, Dian, et al.
Published: (2025)
GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
by: Sun, Zhongtian, et al.
Published: (2025)
by: Sun, Zhongtian, et al.
Published: (2025)
Provably Efficient Information-Directed Sampling Algorithms for Multi-Agent Reinforcement Learning
by: Zhang, Qiaosheng, et al.
Published: (2024)
by: Zhang, Qiaosheng, et al.
Published: (2024)
A Sheaf-Theoretic and Topological Perspective on Complex Network Modeling and Attention Mechanisms in Graph Neural Models
by: Hu, Chuan-Shen
Published: (2026)
by: Hu, Chuan-Shen
Published: (2026)
Graph Feedback Bandits on Similar Arms: With and Without Graph Structures
by: Qi, Han, et al.
Published: (2025)
by: Qi, Han, et al.
Published: (2025)
Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks
by: Wang, Chaojie, et al.
Published: (2024)
by: Wang, Chaojie, et al.
Published: (2024)
Learn Beneficial Noise as Graph Augmentation
by: Huang, Siqi, et al.
Published: (2025)
by: Huang, Siqi, et al.
Published: (2025)
Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity
by: Zhang, Hangfan, et al.
Published: (2025)
by: Zhang, Hangfan, et al.
Published: (2025)
Quantum Graph Attention Network: A Novel Quantum Multi-Head Attention Mechanism for Graph Learning
by: Ning, An, et al.
Published: (2025)
by: Ning, An, et al.
Published: (2025)
Always Skip Attention
by: Ji, Yiping, et al.
Published: (2025)
by: Ji, Yiping, et al.
Published: (2025)
GSINA: Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention
by: Yan, Junchi, et al.
Published: (2024)
by: Yan, Junchi, et al.
Published: (2024)
Graph World Model
by: Feng, Tao, et al.
Published: (2025)
by: Feng, Tao, et al.
Published: (2025)
Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization
by: Yao, Xinhao, et al.
Published: (2024)
by: Yao, Xinhao, et al.
Published: (2024)
Hierarchical Attention Models for Multi-Relational Graphs
by: Iyer, Roshni G., et al.
Published: (2024)
by: Iyer, Roshni G., et al.
Published: (2024)
Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms
by: Song, Jiyan, et al.
Published: (2026)
by: Song, Jiyan, et al.
Published: (2026)
Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block Models
by: Zhang, Ning, et al.
Published: (2024)
by: Zhang, Ning, et al.
Published: (2024)
SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion
by: Su, Junwei, et al.
Published: (2025)
by: Su, Junwei, et al.
Published: (2025)
Block-Attention for Efficient Prefilling
by: Ma, Dongyang, et al.
Published: (2024)
by: Ma, Dongyang, et al.
Published: (2024)
Graph Structure Inference with BAM: Introducing the Bilinear Attention Mechanism
by: Froehlich, Philipp, et al.
Published: (2024)
by: Froehlich, Philipp, et al.
Published: (2024)
GABIC: Graph-based Attention Block for Image Compression
by: Spadaro, Gabriele, et al.
Published: (2024)
by: Spadaro, Gabriele, et al.
Published: (2024)
Attn-JGNN: Attention Enhanced Join-Graph Neural Networks
by: Zhang, Jixin
Published: (2025)
by: Zhang, Jixin
Published: (2025)
Inductive Power Grid Cascading Failure Analysis with GRU-Gated Graph Attention
by: Zhou, Tianxin, et al.
Published: (2026)
by: Zhou, Tianxin, et al.
Published: (2026)
Towards Mechanistic Interpretability of Graph Transformers via Attention Graphs
by: El, Batu, et al.
Published: (2025)
by: El, Batu, et al.
Published: (2025)
HGATSolver: A Heterogeneous Graph Attention Solver for Fluid-Structure Interaction
by: Zhang, Qin-Yi, et al.
Published: (2026)
by: Zhang, Qin-Yi, et al.
Published: (2026)
Deep Graph Attention Networks
by: Kato, Jun, et al.
Published: (2024)
by: Kato, Jun, et al.
Published: (2024)
Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment
by: Li, Jiajia, et al.
Published: (2026)
by: Li, Jiajia, et al.
Published: (2026)
SFi-Former: Sparse Flow Induced Attention for Graph Transformer
by: Li, Zhonghao, et al.
Published: (2025)
by: Li, Zhonghao, et al.
Published: (2025)
Optimal Inference in Contextual Stochastic Block Models
by: Duranthon, O., et al.
Published: (2023)
by: Duranthon, O., et al.
Published: (2023)
Perturbation Ontology based Graph Attention Networks
by: Wang, Yichen, et al.
Published: (2024)
by: Wang, Yichen, et al.
Published: (2024)
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models
by: Zhang, Yufeng, et al.
Published: (2022)
by: Zhang, Yufeng, et al.
Published: (2022)
TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
by: E, Jiawei, et al.
Published: (2024)
by: E, Jiawei, et al.
Published: (2024)
EGAM: Extended Graph Attention Model for Solving Routing Problems
by: Wang, Licheng, et al.
Published: (2026)
by: Wang, Licheng, et al.
Published: (2026)
Consensus Knowledge Graph Learning via Multi-view Sparse Low Rank Block Model
by: Cai, Tianxi, et al.
Published: (2022)
by: Cai, Tianxi, et al.
Published: (2022)
TempoKGAT: A Novel Graph Attention Network Approach for Temporal Graph Analysis
by: Sasal, Lena, et al.
Published: (2024)
by: Sasal, Lena, et al.
Published: (2024)
Feature Selection via Dynamic Graph-based Attention Block in MI-based EEG Signals
by: Han, Hyeon-Taek, et al.
Published: (2024)
by: Han, Hyeon-Taek, et al.
Published: (2024)
Similar Items
-
Gated Graph Attention Networks with Learnable Temperature
by: Ma, Zhongtian, et al.
Published: (2026) -
Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability
by: Zhang, Yexin, et al.
Published: (2026) -
Community Detection in the Multi-View Stochastic Block Model
by: Zhang, Yexin, et al.
Published: (2024) -
Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms
by: Ma, Zhongtian, et al.
Published: (2024) -
Is Graph Convolution Always Beneficial For Every Feature?
by: Zheng, Yilun, et al.
Published: (2024)