Daixin Wang

39 papers A* 12A 3Journal 16Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
APL-LLM: adaptive pseudo-labeling with large language models for few-shot node classification.
Frontiers Comput. Sci.
Junyi Li, Chenweinan Jiang, Daixin Wang, Guo Ye, Libang Zhang, Huimei He, Binbin Hu, Zhiqiang Zhang, Fuzhen Zhuang
2026 J jnl
When Sharpening Becomes Collapse: Sampling Bias and Semantic Coupling in RL with Verifiable Rewards.
CoRR
Mingyuan Fan, Weiguang Han, Daixin Wang, Cen Chen, Zhiqiang Zhang, Jun Zhou
2025 J jnl
Chaotic Dynamics and Self-Recovery Control for a Magnetic-Levitation Spacecraft Under Single-Rod Fault.
IEEE Trans. Aerosp. Electron. Syst.
He Liao, Daixin Wang, Jinjin Xie, Yi Xu, Chuang Yao, Zhongxing Tang
2025 — conf
Constrained Optimization to Improve Critical Rare Classes Performance Within the Top-Ranking Part.
ECML/PKDD (1)
Yuxin Ying, Fuzhen Zhuang, Ziyi Liu, Dingyuan Zhu, Daixin Wang, Xiaobo Qin
2025 — conf
Enhanced Insurance Claim Prediction via Decoupled Graph Neural Networks with Pseudo Labeling.
KDD (2)
Hongrui Liu, Daixin Wang, Yifan Wu, Zhiqiang Zhang, Xiaobo Qin
2025 — conf
FLAG: Fraud Detection with LLM-enhanced Graph Neural Network.
KDD (2)
Chengdong Yang, Hongrui Liu, Daixin Wang, Zhiqiang Zhang, Cheng Yang, Chuan Shi
2025 A* conf
IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification.
WWW
Zhixun Li, Dingshuo Chen, Tong Zhao, Daixin Wang, Hongrui Liu, Zhiqiang Zhang, Jun Zhou, Jeffrey Xu Yu
2025 J jnl
IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification.
CoRR
Zhixun Li, Dingshuo Chen, Tong Zhao, Daixin Wang, Hongrui Liu, Zhiqiang Zhang, Jun Zhou, Jeffrey Xu Yu
2025 J jnl
Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging.
CoRR
Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang
2025 A* conf
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation.
AAAI
Wei Chen, Guo Ye, Yakun Wang, Zhao Zhang, Libang Zhang, Daixin Wang, Zhiqiang Zhang, Fuzhen Zhuang
2025 — conf
Stable Representation Learning on Graphs from Multiple Environments with Structure Distribution Shift.
KDD (1)
Tong Zhao, Daixin Wang, Zhiqiang Zhang, Yulin Kang, Jun Zhou
2025 — conf
Whitening-based Adversarial Bi-Regressor for Cross-platform Insurance Claims Prediction.
WWW (Companion Volume)
Xiaoyu Liu, Yiqing Wu, Dingyuan Zhu, Yifan Wu, Daixin Wang, Xiaobo Qin, Fuzhen Zhuang
2024 J jnl
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning.
CoRR
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
2024 — conf
Granola: Graph Neural Network Tackling Tabular Data for Online Loan Default Prediction.
DASFAA (7)
Borui Ye, Shuo Yang, Meiqi Zhu, Binbin Hu, Daixin Wang, Zhiqiang Zhang, Youqiang He, Zhiyang Hu, Huimei He, Jun Zhou
2024 J jnl
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.
CoRR
Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou
2024 A* conf
Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement.
KDD
Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang
2024 J jnl
Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement.
CoRR
Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang
2024 J jnl
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification.
IEEE Trans. Knowl. Data Eng.
Xin Wang, Heng Chang, Beini Xie, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu
2024 J jnl
Wealth Distribution Involving Psychological Traits and Non-Maxwellian Collision Kernel.
Entropy
Daixin Wang, Shaoyong Lai
2023 A* conf
Adversarially Robust Neural Architecture Search for Graph Neural Networks.
CVPR
Beini Xie, Heng Chang, Ziwei Zhang, Xin Wang, Daixin Wang, Zhiqiang Zhang, Rex Ying, Wenwu Zhu
2023 J jnl
Adversarially Robust Neural Architecture Search for Graph Neural Networks.
CoRR
Beini Xie, Heng Chang, Ziwei Zhang, Xin Wang, Daixin Wang, Zhiqiang Zhang, Rex Ying, Wenwu Zhu
2023 A* conf
Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning.
KDD
Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou
2023 A* conf
Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.
WWW
Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou
2023 — conf
Unsupervised Fraud Transaction Detection on Dynamic Attributed Networks.
DASFAA (4)
Yangyang Hou, Daixin Wang, Binbin Hu, Ruoyu Zhuang, Zhiqiang Zhang, Jun Zhou, Feng Zhao, Yulin Kang, Zhanwen Qiao
2022 A* conf
A Graph Learning Based Framework for Billion-Scale Offline User Identification.
KDD
Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou
2022 J jnl
Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification.
CoRR
Beini Xie, Heng Chang, Xin Wang, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu
2021 J jnl
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation.
CoRR
Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu
2021 A conf
Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation.
CIKM
Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu
2021 A conf
Low-dimensional Alignment for Cross-Domain Recommendation.
CIKM
Tianxin Wang, Fuzhen Zhuang, Zhiqiang Zhang, Daixin Wang, Jun Zhou, Qing He
2021 A conf
Temporal-Aware Graph Neural Network for Credit Risk Prediction.
SDM
Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi
2020 J jnl
A Semi-supervised Graph Attentive Network for Financial Fraud Detection.
CoRR
Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang, Yuan Qi
2020 J jnl
RNE: A Scalable Network Embedding for Billion-scale Recommendation.
CoRR
Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan Qi
2019 A* conf
A Semi-Supervised Graph Attentive Network for Financial Fraud Detection.
ICDM
Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang
2019 — conf
RNE: A Scalable Network Embedding for Billion-Scale Recommendation.
PAKDD (2)
Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi
2018 A* conf
Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation.
AAAI
Daixin Wang, Peng Cui, Wenwu Zhu
2018 A* conf
Deep Variational Network Embedding in Wasserstein Space.
KDD
Dingyuan Zhu, Peng Cui, Daixin Wang, Wenwu Zhu
2016 A* conf
Structural Deep Network Embedding.
KDD
Daixin Wang, Peng Cui, Wenwu Zhu
2015 A* conf
Deep Multimodal Hashing with Orthogonal Regularization.
IJCAI
Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu
2015 J jnl
Learning Compact Hash Codes for Multimodal Representations Using Orthogonal Deep Structure.
IEEE Trans. Multim.
Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu