DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling
Fuente:
arXiv
Saved in:
| Main Authors: | Liao, Ningyi, Yu, Zihao, Luo, Siqiang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
by: Liao, Ningyi, et al.
Published: (2024)
by: Liao, Ningyi, et al.
Published: (2024)
SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation
by: Liu, Haoyu, et al.
Published: (2023)
by: Liu, Haoyu, et al.
Published: (2023)
FedGT: Federated Node Classification with Scalable Graph Transformer
by: Zhang, Zaixi, et al.
Published: (2024)
by: Zhang, Zaixi, et al.
Published: (2024)
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
by: Liao, Ningyi, et al.
Published: (2024)
by: Liao, Ningyi, et al.
Published: (2024)
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)
by: Cheng, Yao, et al.
Published: (2023)
Coden: Efficient Temporal Graph Neural Networks for Continuous Prediction
by: Zhu, Zulun, et al.
Published: (2026)
by: Zhu, Zulun, et al.
Published: (2026)
AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers
by: Zhu, Wenhao, et al.
Published: (2024)
by: Zhu, Wenhao, et al.
Published: (2024)
Modality-free Graph In-context Alignment
by: Zhuo, Wei, et al.
Published: (2026)
by: Zhuo, Wei, et al.
Published: (2026)
FairGT: A Fairness-aware Graph Transformer
by: Luo, Renqiang, et al.
Published: (2024)
by: Luo, Renqiang, et al.
Published: (2024)
CAMAL: Optimizing LSM-trees via Active Learning
by: Yu, Weiping, et al.
Published: (2024)
by: Yu, Weiping, et al.
Published: (2024)
OpenGT: A Comprehensive Benchmark For Graph Transformers
by: Tang, Jiachen, et al.
Published: (2025)
by: Tang, Jiachen, et al.
Published: (2025)
Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
by: Wang, Kai, et al.
Published: (2024)
by: Wang, Kai, et al.
Published: (2024)
MoSE: Unveiling Structural Patterns in Graphs via Mixture of Subgraph Experts
by: Ye, Junda, et al.
Published: (2025)
by: Ye, Junda, et al.
Published: (2025)
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
by: Luo, Renqiang, et al.
Published: (2024)
by: Luo, Renqiang, et al.
Published: (2024)
DARTS-GT: Differentiable Architecture Search for Graph Transformers with Quantifiable Instance-Specific Interpretability Analysis
by: Chakraborty, Shruti Sarika, et al.
Published: (2025)
by: Chakraborty, Shruti Sarika, et al.
Published: (2025)
DAM-GT: Dual Positional Encoding-Based Attention Masking Graph Transformer for Node Classification
by: Li, Chenyang, et al.
Published: (2025)
by: Li, Chenyang, et al.
Published: (2025)
RAGDoll: Efficient Offloading-based Online RAG System on a Single GPU
by: Yu, Weiping, et al.
Published: (2025)
by: Yu, Weiping, et al.
Published: (2025)
Online Continual Learning with Dynamic Label Hierarchies
by: Wang, Xinrui, et al.
Published: (2026)
by: Wang, Xinrui, et al.
Published: (2026)
tsGT: Stochastic Time Series Modeling With Transformer
by: Kuciński, Łukasz, et al.
Published: (2024)
by: Kuciński, Łukasz, et al.
Published: (2024)
Flatten Graphs as Sequences: Transformers are Scalable Graph Generators
by: Chen, Dexiong, et al.
Published: (2025)
by: Chen, Dexiong, et al.
Published: (2025)
Learning Label Hierarchy with Supervised Contrastive Learning
by: Lian, Ruixue, et al.
Published: (2024)
by: Lian, Ruixue, et al.
Published: (2024)
Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
by: Jia, Ziqi, et al.
Published: (2024)
by: Jia, Ziqi, et al.
Published: (2024)
TorchGT: A Holistic System for Large-scale Graph Transformer Training
by: Zhang, Meng, et al.
Published: (2024)
by: Zhang, Meng, et al.
Published: (2024)
Scalable Label Distribution Learning for Multi-Label Classification
by: Zhao, Xingyu, et al.
Published: (2023)
by: Zhao, Xingyu, et al.
Published: (2023)
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024)
by: Gong, Chenghua, et al.
Published: (2024)
Decoupling the Class Label and the Target Concept in Machine Unlearning
by: Zhu, Jianing, et al.
Published: (2024)
by: Zhu, Jianing, et al.
Published: (2024)
DNS-GT: A Graph-based Transformer Approach to Learn Embeddings of Domain Names from DNS Queries
by: Altieri, Massimiliano, et al.
Published: (2026)
by: Altieri, Massimiliano, et al.
Published: (2026)
Translational Gaps in Graph Transformers for Longitudinal EHR Prediction: A Critical Appraisal of GT-BEHRT
by: Tadigotla, Krish
Published: (2026)
by: Tadigotla, Krish
Published: (2026)
GT-SNT: A Linear-Time Transformer for Large-Scale Graphs via Spiking Node Tokenization
by: Zhang, Huizhe, et al.
Published: (2025)
by: Zhang, Huizhe, et al.
Published: (2025)
Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classification
by: Yu, Simon, et al.
Published: (2023)
by: Yu, Simon, et al.
Published: (2023)
Augmenting Knowledge Graph Hierarchies Using Neural Transformers
by: Sharma, Sanat, et al.
Published: (2024)
by: Sharma, Sanat, et al.
Published: (2024)
Hierarchy-Consistent Learning and Adaptive Loss Balancing for Hierarchical Multi-Label Classification
by: Jiang, Ruobing, et al.
Published: (2025)
by: Jiang, Ruobing, et al.
Published: (2025)
Constraint-Enhanced Reinforcement Learning Based on Dynamic Decoupled Spherical Radial Squashing
by: Liao, Qijun, et al.
Published: (2026)
by: Liao, Qijun, et al.
Published: (2026)
GIST: Gauge-Invariant Spectral Transformers for Scalable Graph Neural Operators
by: Rigotti, Mattia, et al.
Published: (2026)
by: Rigotti, Mattia, et al.
Published: (2026)
A Scalable and Effective Alternative to Graph Transformers
by: Sancak, Kaan, et al.
Published: (2024)
by: Sancak, Kaan, et al.
Published: (2024)
Graph Transformer with Disease Subgraph Positional Encoding for Improved Comorbidity Prediction
by: Qin, Xihan, et al.
Published: (2025)
by: Qin, Xihan, et al.
Published: (2025)
Balancing Label Quantity and Quality for Scalable Elicitation
by: Mallen, Alex, et al.
Published: (2024)
by: Mallen, Alex, et al.
Published: (2024)
Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling
by: Luo, Yuhong, et al.
Published: (2024)
by: Luo, Yuhong, et al.
Published: (2024)
Expander Hierarchies for Normalized Cuts on Graphs
by: Hanauer, Kathrin, et al.
Published: (2024)
by: Hanauer, Kathrin, et al.
Published: (2024)
Distributed Graph Embedding with Information-Oriented Random Walks
by: Fang, Peng, et al.
Published: (2023)
by: Fang, Peng, et al.
Published: (2023)
Similar Items
-
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
by: Liao, Ningyi, et al.
Published: (2024) -
SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation
by: Liu, Haoyu, et al.
Published: (2023) -
FedGT: Federated Node Classification with Scalable Graph Transformer
by: Zhang, Zaixi, et al.
Published: (2024) -
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
by: Liao, Ningyi, et al.
Published: (2024) -
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)