Saved in:
| Main Authors: | Yang, Yuhan, Fu, Xingbo, Li, Jundong |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.23469 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Edge Prompt Tuning for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023)
by: Dong, Yushun, et al.
Published: (2023)
Adversarial Attacks on Fairness of Graph Neural Networks
by: Zhang, Binchi, et al.
Published: (2023)
by: Zhang, Binchi, et al.
Published: (2023)
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach
by: Li, Yicong, et al.
Published: (2024)
by: Li, Yicong, et al.
Published: (2024)
Improving Fairness in Graph Neural Networks via Counterfactual Debiasing
by: Wo, Zengyi, et al.
Published: (2025)
by: Wo, Zengyi, et al.
Published: (2025)
Graph Prompting for Graph Learning Models: Recent Advances and Future Directions
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Federated Graph Learning with Structure Proxy Alignment
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
by: Chen, Zihan, et al.
Published: (2025)
by: Chen, Zihan, et al.
Published: (2025)
Federated Graph Learning with Graphless Clients
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
Instance-Aware Graph Prompt Learning
by: Li, Jiazheng, et al.
Published: (2024)
by: Li, Jiazheng, et al.
Published: (2024)
Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks
by: Lee, Yeon-Chang, et al.
Published: (2024)
by: Lee, Yeon-Chang, et al.
Published: (2024)
Benchmarking Fairness-aware Graph Neural Networks in Knowledge Graphs
by: Sasaki, Yuya
Published: (2025)
by: Sasaki, Yuya
Published: (2025)
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage
by: Song, Ying, et al.
Published: (2024)
by: Song, Ying, et al.
Published: (2024)
Spectral Greedy Coresets for Graph Neural Networks
by: Ding, Mucong, et al.
Published: (2024)
by: Ding, Mucong, et al.
Published: (2024)
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning
by: Fu, Xingbo, et al.
Published: (2024)
by: Fu, Xingbo, et al.
Published: (2024)
Equipping Federated Graph Neural Networks with Structure-aware Group Fairness
by: Cui, Nan, et al.
Published: (2023)
by: Cui, Nan, et al.
Published: (2023)
FnRGNN: Distribution-aware Fairness in Graph Neural Network
by: Park, Soyoung, et al.
Published: (2025)
by: Park, Soyoung, et al.
Published: (2025)
FairGU: Fairness-aware Graph Unlearning in Social Networks
by: Luo, Renqiang, et al.
Published: (2026)
by: Luo, Renqiang, et al.
Published: (2026)
Loss-aware Curriculum Learning for Heterogeneous Graph Neural Networks
by: Wong, Zhen Hao, et al.
Published: (2024)
by: Wong, Zhen Hao, et al.
Published: (2024)
Fairness-aware Vision Transformer via Debiased Self-Attention
by: Qiang, Yao, et al.
Published: (2023)
by: Qiang, Yao, et al.
Published: (2023)
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
Dual-Frequency Filtering Self-aware Graph Neural Networks for Homophilic and Heterophilic Graphs
by: Yang, Yachao, et al.
Published: (2024)
by: Yang, Yachao, et al.
Published: (2024)
Homophily-aware Supervised Contrastive Counterfactual Augmented Fair Graph Neural Network
by: Kejani, Mahdi Tavassoli, et al.
Published: (2026)
by: Kejani, Mahdi Tavassoli, et al.
Published: (2026)
Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing
by: Liu, Yezi, et al.
Published: (2025)
by: Liu, Yezi, et al.
Published: (2025)
Safety in Graph Machine Learning: Threats and Safeguards
by: Wang, Song, et al.
Published: (2024)
by: Wang, Song, et al.
Published: (2024)
Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
by: Liu, Haochen, et al.
Published: (2025)
by: Liu, Haochen, et al.
Published: (2025)
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
by: Li, Chengyu, et al.
Published: (2024)
by: Li, Chengyu, et al.
Published: (2024)
MAGPrompt: Message-Adaptive Graph Prompt Tuning for Graph Neural Networks
by: Nguyen, Long D., et al.
Published: (2026)
by: Nguyen, Long D., et al.
Published: (2026)
FairGC: Fairness-aware Graph Condensation
by: Gao, Yihan, et al.
Published: (2026)
by: Gao, Yihan, et al.
Published: (2026)
Towards Certified Unlearning for Deep Neural Networks
by: Zhang, Binchi, et al.
Published: (2024)
by: Zhang, Binchi, et al.
Published: (2024)
ComFairGNN: Community Fair Graph Neural Network
by: Sium, Yonas, et al.
Published: (2024)
by: Sium, Yonas, et al.
Published: (2024)
Adaptive Progressive Attention Graph Neural Network for EEG Emotion Recognition
by: Feng, Tianzhi, et al.
Published: (2025)
by: Feng, Tianzhi, et al.
Published: (2025)
Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks
by: Openja, Moses, et al.
Published: (2025)
by: Openja, Moses, et al.
Published: (2025)
A Benchmark for Fairness-Aware Graph Learning
by: Dong, Yushun, et al.
Published: (2024)
by: Dong, Yushun, et al.
Published: (2024)
Prompt-based Unifying Inference Attack on Graph Neural Networks
by: Wei, Yuecen, et al.
Published: (2024)
by: Wei, Yuecen, et al.
Published: (2024)
DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback
by: Wu, Yiqing, et al.
Published: (2024)
by: Wu, Yiqing, et al.
Published: (2024)
Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022)
by: Fang, Taoran, et al.
Published: (2022)
Dual-Channel Multiplex Graph Neural Networks for Recommendation
by: Li, Xiang, et al.
Published: (2024)
by: Li, Xiang, et al.
Published: (2024)
Similar Items
-
Edge Prompt Tuning for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025) -
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025) -
Certified Defense on the Fairness of Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2023) -
Adversarial Attacks on Fairness of Graph Neural Networks
by: Zhang, Binchi, et al.
Published: (2023) -
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach
by: Li, Yicong, et al.
Published: (2024)