Suhang Wang

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 221

Top Venues

Publications

Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma
Active Learning for Graphs with Noisy Structures. CoRR (2024)
Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Suhang Wang, Yu Meng, Jiawei Han
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. CoRR (2024)
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Interpretable Imitation Learning with Dynamic Causal Relations. WSDM (2024)
Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. CoRR (2024)
Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang
Universal Prompt Optimizer for Safe Text-to-Image Generation. CoRR (2024)
Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. KDD (2024)
Fali Wang, Tianxiang Zhao, Suhang Wang
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR (2024)
Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. CoRR (2024)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR (2024)
Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. CoRR (2024)
Teng Xiao, Suhang Wang
Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback. CoRR (2024)
Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang
Universal Prompt Optimizer for Safe Text-to-Image Generation. NAACL-HLT (2024)
Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danqing Zhang, Monica Xiao Cheng, Bing Yin, Jasha Droppo, Suhang Wang, Jing Gao
LightLT: A Lightweight Representation Quantization Framework for Long-Tail Data. ICDE (2024)
Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. ACL (Findings) (2024)
Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang
Hierarchical Query Classification in E-commerce Search. WWW (Companion Volume) (2024)
Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. CoRR (2024)
Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang
Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR (2024)
Fali Wang, Tianxiang Zhao, Suhang Wang
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM (2024)
Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma
Active Learning for Graphs with Noisy Structures. SDM (2024)
Xianren Zhang, Dongwon Lee, Suhang Wang
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. CoRR (2024)
Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR (2024)
Tianxiang Zhao, Xiang Zhang, Suhang Wang
Disambiguated Node Classification with Graph Neural Networks. WWW (2024)
Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang
Spectral-based Graph Neural Networks for Complementary Item Recommendation. CoRR (2024)
Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang
Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks. CoRR (2024)
Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang
Spectral-Based Graph Neural Networks for Complementary Item Recommendation. AAAI (2024)
Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. CoRR (2024)
Tianxiang Zhao, Xiang Zhang, Suhang Wang
Disambiguated Node Classification with Graph Neural Networks. CoRR (2024)
Enyan Dai, Minhua Lin, Suhang Wang
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection. CoRR (2024)
Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. KDD (2024)
Yang Li, Dongrui Wu, Suhang Wang
Future-generation attack and defense in neural networks. Future Gener. Comput. Syst. 152 (2024)
Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. ICLR (2024)
Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning. CoRR (2024)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD (2024)
Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang
Hierarchical Query Classification in E-commerce Search. CoRR (2024)
Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang
Learning Graph Filters for Spectral GNNs via Newton Interpolation. CoRR (2023)
Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. CoRR (2023)
Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
Simple and Asymmetric Graph Contrastive Learning without Augmentations. CoRR (2023)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR (2023)
Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. KDD (2023)
Huaisheng Zhu, Guoji Fu, Zhimeng Guo, Zhiwei Zhang, Teng Xiao, Suhang Wang
Fairness-aware Message Passing for Graph Neural Networks. CoRR (2023)
Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Cheng, Bing Yin, Suhang Wang, Philip S. Yu
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD (2023)
Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang
Learning How to Propagate Messages in Graph Neural Networks. CoRR (2023)
Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Cheng, Bing Yin, Suhang Wang
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. CoRR (2023)
Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang
Certifiably Robust Graph Contrastive Learning. CoRR (2023)
Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang
Learning fair models without sensitive attributes: A generative approach. Neurocomputing 561 (2023)
Yitang Wang, Suhang Wang, Yong Pang, Xueguan Song
Outlier Detection and Correction for Time Series Data of Tunnel Boring Machine. ICIRA (6) (2023)
Teng Xiao, Zhengyu Chen, Suhang Wang
Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. KDD (2023)
Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. RecSys (2023)
Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang
Self-Explainable Graph Neural Networks for Link Prediction. CoRR (2023)
Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria
Recent Developments in Recommender Systems: A Survey. CoRR (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR (2023)
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD (2023)
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR (2023)
Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang
Unnoticeable Backdoor Attacks on Graph Neural Networks. CoRR (2023)
Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. NeurIPS (2023)
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR (2023)
Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang
You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) (2023)
Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang
Counterfactual Learning on Graphs: A Survey. CoRR (2023)
Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. CoRR (2023)
Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang
Unnoticeable Backdoor Attacks on Graph Neural Networks. WWW (2023)
Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang
Towards Fair Graph Neural Networks via Graph Counterfactual. CIKM (2023)
Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
Simple and Asymmetric Graph Contrastive Learning without Augmentations. NeurIPS (2023)
Enyan Dai, Suhang Wang
Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information. IEEE Trans. Knowl. Data Eng. 35 (7) (2023)
Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang
Language Models As Semantic Indexers. CoRR (2023)
Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal
Jointly Attacking Graph Neural Network and its Explanations. ICDE (2023)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM (2023)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14 (5) (2023)
Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang
Certifiably Robust Graph Contrastive Learning. NeurIPS (2023)
Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang
HP-GMN: Graph Memory Networks for Heterophilous Graphs. CoRR (2022)
Tianxiang Zhao, Xiang Zhang, Suhang Wang
Exploring Edge Disentanglement for Node Classification. CoRR (2022)
Tianxiang Zhao, Xiang Zhang, Suhang Wang
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR (2022)
Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang
HP-GMN: Graph Memory Networks for Heterophilous Graphs. ICDM (2022)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
On Consistency in Graph Neural Network Interpretation. CoRR (2022)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG (2022)
Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR (2022)
Teng Xiao, Suhang Wang
Towards Unbiased and Robust Causal Ranking for Recommender Systems. WSDM (2022)
Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM (2022)
Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang
Label-Wise Graph Convolutional Network for Heterophilic Graphs. LoG (2022)
Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR (2022)
Wen Zhang, B. Blair Braden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang
Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning. Neuroinformatics 20 (2) (2022)
Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
Decoupled Self-supervised Learning for Non-Homophilous Graphs. CoRR (2022)
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR (2022)
Teng Xiao, Zhengyu Chen, Suhang Wang
Towards Bridging Algorithm and Theory for Unbiased Recommendation. CoRR (2022)
Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. CoRR (2022)
Tianxiang Zhao, Xiang Zhang, Suhang Wang
Exploring Edge Disentanglement for Node Classification. WWW (2022)
Huaisheng Zhu, Suhang Wang
Learning Fair Models without Sensitive Attributes: A Generative Approach. CoRR (2022)
Teng Xiao, Zhengyu Chen, Suhang Wang
Representation Matters When Learning From Biased Feedback in Recommendation. CIKM (2022)
Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah
Friend Story Ranking with Edge-Contextual Local Graph Convolutions. WSDM (2022)
Enyan Dai, Wei Jin, Hui Liu, Suhang Wang
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. WSDM (2022)
Teng Xiao, Suhang Wang
Towards Off-Policy Learning for Ranking Policies with Logged Feedback. AAAI (2022)
Enyan Dai, Suhang Wang
Towards Prototype-Based Self-Explainable Graph Neural Network. CoRR (2022)
Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
Decoupled Self-supervised Learning for Graphs. NeurIPS (2022)
Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger
Graph routing between capsules. Neural Networks 143 (2021)
Enyan Dai, Suhang Wang
Towards Self-Explainable Graph Neural Network. CIKM (2021)
Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang
Graph Adversarial Attack via Rewiring. KDD (2021)
Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. CoRR (2021)
Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang
Labeled Data Generation with Inexact Supervision. CoRR (2021)
Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar
Functional Autoencoders for Functional Data Representation Learning. SDM (2021)
Enyan Dai, Suhang Wang
Towards Self-Explainable Graph Neural Network. CoRR (2021)
Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang
Semi-Supervised Graph-to-Graph Translation. CoRR (2021)

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Publication Activity (10 Years)

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Suhang Wang