Unsupervised Image Super-Resolution with an Indirect Supervised Path. - Zhen Han; Enyan Dai; Xu Jia 012; Xiaoying Ren; Shuaijun Chen; Chunjing Xu; Jianzhuang Liu; Qi Tian 001 (CoRR, 2019)

TEST_POSITIVE at W-NUT 2020 Shared Task-3: Cross-task modeling. - Chacha Chen; Chieh-Yang Huang; Yaqi Hou; Yang Shi; Enyan Dai; Jiaqi Wang 002 (W-NUT@EMNLP, 2020)

Unsupervised Image Super-Resolution with an Indirect Supervised Path. - Shuaijun Chen; Zhen Han; Enyan Dai; Xu Jia 012; Ziluan Liu; Xing Liu; Xueyi Zou; Chunjing Xu; Jianzhuang Liu; Qi Tian 001 (CVPR Workshops, 2020)

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository. - Enyan Dai; Yiwei Sun; Suhang Wang (ICWSM, 2020)

FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information. - Enyan Dai; Suhang Wang (CoRR, 2020)

TEST_POSITIVE at W-NUT 2020 Shared Task-3: Joint Event Multi-task Learning for Slot Filling in Noisy Text. - Chacha Chen; Chieh-Yang Huang; Yaqi Hou; Yang Shi; Enyan Dai; Jiaqi Wang 002 (CoRR, 2020)

Towards Self-Explainable Graph Neural Network. - Enyan Dai; Suhang Wang (CIKM, 2021)

NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. - Enyan Dai; Charu Aggarwal 001; Suhang Wang (KDD, 2021)

Labeled Data Generation with Inexact Supervision. - Enyan Dai; Kai Shu; Yiwei Sun; Suhang Wang (KDD, 2021)

Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information. - Enyan Dai; Suhang Wang (WSDM, 2021)

You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. - Tianxiang Zhao 001; Enyan Dai; Kai Shu; Suhang Wang (CoRR, 2021)

Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. - Yuqing Hu 002; Xiaoyuan Cheng; Suhang Wang; Jianli Chen; Tianxiang Zhao 001; Enyan Dai (CoRR, 2021)

Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs. - Enyan Dai; Zhimeng Guo; Suhang Wang (CoRR, 2021)

HP-GMN: Graph Memory Networks for Heterophilous Graphs. - Junjie Xu; Enyan Dai; Xiang Zhang 001; Suhang Wang (ICDM, 2022)

Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series. - Enyan Dai; Jie Chen (ICLR, 2022)

Label-Wise Graph Convolutional Network for Heterophilic Graphs. - Enyan Dai; Shijie Zhou; Zhimeng Guo; Suhang Wang (LoG, 2022)

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. - Enyan Dai; Wei Jin 009; Hui Liu 031; Suhang Wang (WSDM, 2022)

Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. - Tianxiang Zhao 001; Enyan Dai; Kai Shu; Suhang Wang (WSDM, 2022)

A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. - Enyan Dai; Limeng Cui; Zhengyang Wang; Xianfeng Tang; Yinghan Wang; Monica Xiao Cheng; Bing Yin; Suhang Wang (KDD, 2023)

Certifiably Robust Graph Contrastive Learning. - Minhua Lin; Teng Xiao; Enyan Dai; Xiang Zhang 001; Suhang Wang (NeurIPS, 2023)

Unnoticeable Backdoor Attacks on Graph Neural Networks. - Enyan Dai; Minhua Lin; Xiang Zhang 001; Suhang Wang (WWW, 2023)

Learning Graph Filters for Spectral GNNs via Newton Interpolation. - Junjie Xu; Enyan Dai; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (CoRR, 2023)

Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information. - Enyan Dai; Suhang Wang (IEEE Trans. Knowl. Data Eng., 2023)

Learning fair models without sensitive attributes: A generative approach. - Huaisheng Zhu; Enyan Dai; Hui Liu 031; Suhang Wang (Neurocomputing, 2023)

Effective Clean-Label Backdoor Attacks on Graph Neural Networks. - Xuanhao Fan; Enyan Dai (CIKM, 2024)

Shape-aware Graph Spectral Learning. - Junjie Xu; Enyan Dai; Dongsheng Luo; Xiang Zhang 001; Suhang Wang (CIKM, 2024)

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. - Zhiwei Zhang; Minhua Lin; Enyan Dai; Suhang Wang (KDD, 2024)

PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection. - Enyan Dai; Minhua Lin; Suhang Wang (CoRR, 2024)

Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks. - Zhiwei Zhang; Minhua Lin; Junjie Xu; Zongyu Wu 001; Enyan Dai; Suhang Wang (CoRR, 2024)

Trojan Prompt Attacks on Graph Neural Networks. - Minhua Lin; Zhiwei Zhang; Enyan Dai; Zongyu Wu 001; Yilong Wang 001; Xiang Zhang 001; Suhang Wang (CoRR, 2024)

Improving Issue-PR Link Prediction via Knowledge-Aware Heterogeneous Graph Learning. - Shuotong Bai; Huaxiao Liu; Enyan Dai; Lei Liu 040 (IEEE Trans. Software Eng., 2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. - Enyan Dai; Tianxiang Zhao 001; Huaisheng Zhu; Junjie Xu; Zhimeng Guo; Hui Liu 031; Jiliang Tang; Suhang Wang (Mach. Intell. Res., 2024)

Robustness Inspired Graph Backdoor Defense. - Zhiwei Zhang; Minhua Lin; Junjie Xu; Zongyu Wu 001; Enyan Dai; Suhang Wang (ICLR, 2025)

Stealing Training Graphs from Graph Neural Networks. - Minhua Lin; Enyan Dai; Junjie Xu; Jinyuan Jia 001; Xiang Zhang 001; Suhang Wang (KDD (1), 2025)

LiSA: Leveraging Link Recommender to Attack Graph Neural Networks via Subgraph Injection. - Wenlun Zhang; Enyan Dai; Kentaro Yoshioka (PAKDD (4), 2025)

UniZyme: A Unified Protein Cleavage Site Predictor Enhanced with Enzyme Active-Site Knowledge. - Chenao Li; Shuo Yan; Enyan Dai (CoRR, 2025)

LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models. - Zongyu Wu 001; Yuwei Niu; Hongcheng Gao; Minhua Lin; Zhiwei Zhang; Zhifang Zhang; Qi Shi; Yilong Wang 001; Sike Fu; Junjie Xu; Junjie Ao; Enyan Dai; et al. (CoRR, 2025)

Towards Prototype-Based Self-Explainable Graph Neural Network. - Enyan Dai; Suhang Wang (ACM Trans. Knowl. Discov. Data, 2025)

Fairness in Graph Learning Augmented with Machine Learning: A Survey. - Renqiang Luo; Ziqi Xu; Xikun Zhang 007; Qing Qing; Huafei Huang; Enyan Dai; Zhe Wang; Bo Yang (CoRR, 2025)

DuFFin: A Dual-Level Fingerprinting Framework for LLMs IP Protection. - Yuliang Yan; Haochun Tang; Shuo Yan; Enyan Dai (CoRR, 2025)

Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications. - Shuo Yan; Yuliang Yan; Bin Ma; Chenao Li; Haochun Tang; Jiahua Lu; Minhua Lin; Yuyuan Feng; Hui Xiong; Enyan Dai (CoRR, 2025)

How Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment. - Bin Ma; Yuyuan Feng; Minhua Lin; Enyan Dai (CoRR, 2025)