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2103.02885
Cited By
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework
The Web Conference (WWW), 2021
4 March 2021
Cheng Yang
Jiawei Liu
C. Shi
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Papers citing
"Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework"
50 / 67 papers shown
Enhancing Graph Neural Networks: A Mutual Learning Approach
Paul Agbaje
Akajyoti Mitra
Afia Anjum
Pranali Khose
Ebelechukwu Nwafor
Habeeb Olufowobi
207
0
0
22 Oct 2025
Efficient Graph Knowledge Distillation from GNNs to Kolmogorov--Arnold Networks via Self-Attention Dynamic Sampling
Can Cui
Zilong Fu
Penghe Huang
Yuanyuan Li
Wu Deng
Dongyan Li
136
0
0
30 Aug 2025
Deterministic Certification of Graph Neural Networks against Graph Poisoning Attacks with Arbitrary Perturbations
Computer Vision and Pattern Recognition (CVPR), 2025
Jiate Li
Meng Pang
Yun Dong
Binghui Wang
AAML
358
1
0
24 Mar 2025
AGNNCert: Defending Graph Neural Networks against Arbitrary Perturbations with Deterministic Certification
Jiate Li
Binghui Wang
AAML
401
3
0
02 Feb 2025
Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature Review
ACM Computing Surveys (ACM CSUR), 2024
Giovanni Ciatto
Federico Sabbatini
Andrea Agiollo
Matteo Magnini
Andrea Omicini
409
35
0
28 Jan 2025
Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence
Liekang Zeng
Shengyuan Ye
Xu Chen
Xiaoxi Zhang
Ju Ren
Jian Tang
Yang Yang
Xuemin
Shen
554
13
0
08 Jan 2025
Training MLPs on Graphs without Supervision
Web Search and Data Mining (WSDM), 2024
Zehong Wang
Zheyuan Zhang
Chuxu Zhang
Yanfang Ye
304
19
0
05 Dec 2024
Winemaking: Extracting Essential Insights for Efficient Threat Detection in Audit Logs
Weiheng Wu
Wei Qiao
Wenhao Yan
Bo-Sian Jiang
Yuling Liu
Baoxu Liu
Zhigang Lu
JunRong Liu
333
0
0
05 Nov 2024
EasyST: A Simple Framework for Spatio-Temporal Prediction
International Conference on Information and Knowledge Management (CIKM), 2024
J. Tang
Wei Wei
Lianghao Xia
Chao Huang
374
9
0
10 Sep 2024
Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation
Lirong Wu
Yunfan Liu
Haitao Lin
Yufei Huang
Stan Z. Li
242
9
0
20 Jul 2024
Graph Knowledge Distillation to Mixture of Experts
Pavel Rumiantsev
Mark Coates
299
1
0
17 Jun 2024
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning
Junjie Xu
Zongyu Wu
Min Lin
Xiang Zhang
Suhang Wang
386
20
0
03 Jun 2024
AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
Knowledge Discovery and Data Mining (KDD), 2024
Weigang Lu
Ziyu Guan
Ziyu Guan
Yaming Yang
264
17
0
23 May 2024
Acceleration Algorithms in GNNs: A Survey
Lu Ma
Zeang Sheng
Miao Hu
Xin Gao
Zhezheng Hao
Ling Yang
Wentao Zhang
Tengjiao Wang
GNN
416
0
0
07 May 2024
E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification
Xin Zhang
Daochen Zha
Qiaoyu Tan
267
2
0
06 May 2024
A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation
Lirong Wu
Haitao Lin
Zhangyang Gao
Guojiang Zhao
Stan Z. Li
220
23
0
06 Mar 2024
On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving
Kaituo Feng
Changsheng Li
Dongchun Ren
Ye Yuan
Guoren Wang
404
15
0
02 Mar 2024
Teaching MLP More Graph Information: A Three-stage Multitask Knowledge Distillation Framework
Junxian Li
Bin Shi
Erfei Cui
Hua Wei
Qinghua Zheng
330
1
0
02 Mar 2024
Graph Inference Acceleration by Learning MLPs on Graphs without Supervision
Zehong Wang
Zheyuan Zhang
Chuxu Zhang
Yanfang Ye
223
0
0
14 Feb 2024
Classifying Nodes in Graphs without GNNs
Daniel Winter
Niv Cohen
Yedid Hoshen
371
3
0
08 Feb 2024
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for
100
×
100\times
100
×
Faster Inference
Yifan Feng
Yihe Luo
Shihui Ying
Yue Gao
BDL
415
7
0
06 Feb 2024
Knowledge Distillation on Spatial-Temporal Graph Convolutional Network for Traffic Prediction
International Journal of Computer Applications (IJCA), 2024
Mohammad Izadi
M. Safayani
Abdolreza Mirzaei
352
9
0
22 Jan 2024
A Survey on Efficient Federated Learning Methods for Foundation Model Training
International Joint Conference on Artificial Intelligence (IJCAI), 2024
Herbert Woisetschläger
Alexander Isenko
Shiqiang Wang
R. Mayer
Hans-Arno Jacobsen
FedML
386
43
0
09 Jan 2024
Propagate & Distill: Towards Effective Graph Learners Using Propagation-Embracing MLPs
Yong-Min Shin
Won-Yong Shin
235
4
0
29 Nov 2023
Unveiling the Unseen Potential of Graph Learning through MLPs: Effective Graph Learners Using Propagation-Embracing MLPs
Yong-Min Shin
Won-Yong Shin
228
1
0
20 Nov 2023
Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation
IEEE International Conference on Data Engineering (ICDE), 2023
Xin Gao
Wentao Zhang
Junliang Yu
Yingxiao Shao
Quoc Viet Hung Nguyen
Tengjiao Wang
Hongzhi Yin
AI4CE
GNN
481
19
0
17 Oct 2023
Data-centric Graph Learning: A Survey
IEEE Transactions on Big Data (IEEE Trans. Big Data), 2023
Jixi Liu
Deyu Bo
Cheng Yang
Haoran Dai
Qi Zhang
Yixin Xiao
Yufei Peng
Chuan Shi
GNN
410
35
0
08 Oct 2023
Teacher-Student Architecture for Knowledge Distillation: A Survey
Chengming Hu
Xuan Li
Danyang Liu
Haolun Wu
Xi Chen
Ju Wang
Xue Liu
438
47
0
08 Aug 2023
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
International Conference on Learning Representations (ICLR), 2023
Ling Yang
Ye Tian
Minkai Xu
Zhongyi Liu
Shenda Hong
Wei Qu
Wentao Zhang
Tengjiao Wang
Muhan Zhang
J. Leskovec
338
44
0
04 Aug 2023
Shared Growth of Graph Neural Networks via Prompted Free-direction Knowledge Distillation
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Kaituo Feng
Yikun Miao
Changsheng Li
Ye Yuan
Guoren Wang
464
4
0
02 Jul 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware
Shichang Zhang
Atefeh Sohrabizadeh
Cheng Wan
Zijie Huang
Ziniu Hu
Yewen Wang
Yingyan Lin
Lin
Jason Cong
GNN
OOD
316
33
0
24 Jun 2023
Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs
International Conference on Machine Learning (ICML), 2023
Lirong Wu
Haitao Lin
Yufei Huang
Stan Z. Li
252
47
0
09 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
Neural Information Processing Systems (NeurIPS), 2023
Haitao Mao
Zhikai Chen
Wei Jin
Haoyu Han
Yao Ma
Tong Zhao
Neil Shah
Shucheng Zhou
506
52
0
02 Jun 2023
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework
AAAI Conference on Artificial Intelligence (AAAI), 2023
Lirong Wu
Haitao Lin
Yufei Huang
Tianyu Fan
Stan Z. Li
361
52
0
18 May 2023
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis
V. Ioannidis
Shen Wang
Da Zheng
Soji Adeshina
Jun Ma
Han Zhao
Christos Faloutsos
George Karypis
350
42
0
20 Apr 2023
Multi-label Node Classification On Graph-Structured Data
Tianqi Zhao
Ngan Thi Dong
Alan Hanjalic
Megha Khosla
AI4CE
295
9
0
20 Apr 2023
Graph-based Knowledge Distillation: A survey and experimental evaluation
Jing Liu
Tongya Zheng
Guanzheng Zhang
Qinfen Hao
261
15
0
27 Feb 2023
Knowledge Distillation on Graphs: A Survey
ACM Computing Surveys (ACM Comput. Surv.), 2023
Yijun Tian
Shichao Pei
Xiangliang Zhang
Chuxu Zhang
Nitesh Chawla
304
74
0
01 Feb 2023
RELIANT: Fair Knowledge Distillation for Graph Neural Networks
SDM (SDM), 2023
Yushun Dong
Binchi Zhang
Yiling Yuan
Na Zou
Qi Wang
Jundong Li
422
16
0
03 Jan 2023
Multi-duplicated Characterization of Graph Structures using Information Gain Ratio for Graph Neural Networks
IEEE Access (IEEE Access), 2022
Yuga Oishi
Ken Kaneiwa
305
1
0
24 Dec 2022
Hierarchical Model Selection for Graph Neural Netoworks
IEEE Access (IEEE Access), 2022
Yuga Oishi
Ken Kaneiwa
189
0
0
01 Dec 2022
Efficient Graph Neural Network Inference at Large Scale
Xin-pu Gao
Wentao Zhang
Yingxia Shao
Quoc Viet Hung Nguyen
Tengjiao Wang
Hongzhi Yin
AI4CE
GNN
344
9
0
01 Nov 2022
Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision
Jiongyu Guo
Defang Chen
Can Wang
252
4
0
25 Oct 2022
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
Neural Information Processing Systems (NeurIPS), 2022
Chenxiao Yang
Qitian Wu
Junchi Yan
309
29
0
24 Oct 2022
Toward Multiple Specialty Learners for Explaining GNNs via Online Knowledge Distillation
Tien-Cuong Bui
Van-Duc Le
Wen-Syan Li
S. Cha
243
3
0
20 Oct 2022
SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP
Jie Chen
Shouzhen Chen
Mingyuan Bai
Junbin Gao
Junping Zhang
Jian Pu
242
16
0
18 Oct 2022
Boosting Graph Neural Networks via Adaptive Knowledge Distillation
AAAI Conference on Artificial Intelligence (AAAI), 2022
Zhichun Guo
Chunhui Zhang
Yujie Fan
Yijun Tian
Chuxu Zhang
Nitesh Chawla
334
47
0
12 Oct 2022
Linkless Link Prediction via Relational Distillation
International Conference on Machine Learning (ICML), 2022
Zhichun Guo
William Shiao
Shichang Zhang
Yozen Liu
Nitesh Chawla
Neil Shah
Tong Zhao
455
58
0
11 Oct 2022
Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification
Lirong Wu
Jun Xia
Haitao Lin
Zhangyang Gao
Zicheng Liu
Guojiang Zhao
Stan Z. Li
584
8
0
05 Oct 2022
Toward Robust Graph Semi-Supervised Learning against Extreme Data Scarcity
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Kaize Ding
E. Nouri
Guoqing Zheng
Huan Liu
Ryen W. White
297
16
0
26 Aug 2022
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