Research on discovering deep web entries. - Ying Wang 009; Huilai Li; Wanli Zuo; Fengling He; Xin Wang 035; Kerui Chen (Comput. Sci. Inf. Syst., 2011)

Research on Web Query Translation based on Ontology. - Xin Wang 035; Ying Wang 009 (J. Softw., 2012)

Modeling Status Theory in Trust Prediction. - Ying Wang 009; Xin Wang 035; Jiliang Tang; Wanli Zuo; Guoyong Cai (AAAI, 2015)

Exploring Social Context for Topic Identification in Short and Noisy Texts. - Xin Wang 035; Ying Wang 009; Wanli Zuo; Guoyong Cai (AAAI, 2015)

Research on Trust Prediction from a Sociological Perspective. - Ying Wang 009; Xin Wang 035; Wanli Zuo (J. Comput. Sci. Technol., 2015)

Predicting Trust Relationships in Social Networks Based on WKNN. - Qiuyue Zhao; Wanli Zuo; Zhongsheng Tian; Xin Wang 035; Ying Wang 009 (J. Softw., 2015)

Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust. - Xin Wang 035; Ying Wang 009; Hongbin Sun (Comput. Intell. Neurosci., 2016)

Building trust networks in the absence of trust relations. - Xin Wang 035; Ying Wang 009; Jianhua Guo 005 (Frontiers Inf. Technol. Electron. Eng., 2017)

Explanation Chains Model Based on the Fine-Grained Data. - Fuyuan Ma; Wenqi Chen; Min-Hao Xiao; Xin Wang 035; Ying Wang 009 (NLPCC (2), 2019)

Attention-Guide Walk Model in Heterogeneous Information Network for Multi-Style Recommendation Explanation. - Xin Wang 035; Ying Wang 009; Yunzhi Ling (AAAI, 2020)

Traffic Flow Prediction via Spatial Temporal Graph Neural Network. - Xiaoyang Wang; Yao Ma 001; Yiqi Wang 001; Wei Jin 009; Xin Wang 035; Jiliang Tang; Caiyan Jia; Jian Yu 001 (WWW, 2020)

Exploring Common and Label-Specific Features for Multi-Label Learning With Local Label Correlations. - Yunzhi Ling; Ying Wang 009; Xin Wang 035; Yunhao Ling (IEEE Access, 2020)

Exploring Self-training for Imbalanced Node Classification. - Xin Juan; Meixin Peng; Xin Wang 035 (ICONIP (5), 2021)

CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. - Haotian Xue 001; Kaixiong Zhou; Tianlong Chen 001; Kai Guo 003; Xia Hu 001; Yi Chang 001; Xin Wang 035 (CoRR, 2021)

TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network. - Siyuan Guo; Ying Wang 009; Hao Yuan; Zeyu Huang; Jianwei Chen; Xin Wang 035 (Inf. Sci., 2021)

Exploring graph capsual network for graph classification. - Ying Wang 009; Hongji Wang; Hui Jin; Xinrui Huang; Xin Wang 035 (Inf. Sci., 2021)

Orthogonal Graph Neural Networks. - Kai Guo 003; Kaixiong Zhou; Xia Hu 001; Yu Li 022; Yi Chang 001; Xin Wang 035 (AAAI, 2022)

AutoAUG : Automatic Data Augmentation for Graph Neural Networks. - Xiao Liang; Xin Wang 035; Haotian Xue 001; Yintao Yang; Xin Juan; Ying Wang 009 (ACAI, 2022)

Adversarial Training on Weights for Graph Neural Networks. - Haotian Xue 001; Xin Wang 035; Ying Wang 009 (ACAI, 2022)

AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training. - Yili Wang 004; Kaixiong Zhou; Rui Miao 003; Ninghao Liu; Xin Wang 035 (CIKM, 2022)

Cross-Domain Representation Learning for Clothes Unfolding in Robot-Assisted Dressing. - Jinge Qie; Yixing Gao; Runyang Feng; Xin Wang 035; Jielong Yang; Esha Dasgupta; Hyung Jin Chang; Yi Chang 001 (ECCV Workshops (6), 2022)

Towards Unified Representations of Knowledge Graph and Expert Rules for Machine Learning and Reasoning. - Zhepei Wei; Yue Wang 035; Jinnan Li; Zhining Liu 002; Erxin Yu; Yuan Tian 016; Xin Wang 035; Yi Chang 001 (AACL/IJCNLP (1), 2022)

GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks. - Mingchen Sun; Kaixiong Zhou; Xin He 003; Ying Wang 009; Xin Wang 035 (KDD, 2022)

Contrastive Graph Convolutional Networks with adaptive augmentation for text classification. - Yintao Yang; Rui Miao 003; Yili Wang 004; Xin Wang 035 (Inf. Process. Manag., 2022)

Negative samples selecting strategy for graph contrastive learning. - Rui Miao 003; Yintao Yang; Yao Ma 001; Xin Juan; Haotian Xue 001; Jiliang Tang; Ying Wang 009; Xin Wang 035 (Inf. Sci., 2022)

Hierarchical recurrent neural networks for graph generation. - Song Xianduo; Xin Wang 035; Yuyuan Song; Xianglin Zuo; Ying Wang 009 (Inf. Sci., 2022)

Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases. - Yingji Li; Mengnan Du; Xin Wang 035; Ying Wang 009 (ACL (1), 2023)

LAGCL: Towards Stable and Automated Graph Contrastive Learning. - Hengrui Gu 002; Ying Wang 009; Xin Wang 035 (ADMA (3), 2023)

Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation. - Xingyu Zhu 014; Xin Wang 035; Jonathan Freer; Hyung Jin Chang; Yixing Gao (ICRA, 2023)

A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges. - Xuansheng Wu; Kaixiong Zhou; Mingchen Sun; Xin Wang 035; Ninghao Liu (CoRR, 2023)

A Survey on Fairness in Large Language Models. - Yingji Li; Mengnan Du; Rui Song 008; Xin Wang 035; Ying Wang 009 (CoRR, 2023)

INS-GNN: Improving graph imbalance learning with self-supervision. - Xin Juan; Fengfeng Zhou; Wentao Wang 006; Wei Jin 009; Jiliang Tang; Xin Wang 035 (Inf. Sci., 2023)

Structural-aware motif-based prompt tuning for graph clustering. - Mingchen Sun; Mengduo Yang; Yingji Li; Dongmei Mu; Xin Wang 035; Ying Wang 009 (Inf. Sci., 2023)

Generating real-world hypergraphs via deep generative models. - Xianglin Zuo; Wenqi Chen; Song Xianduo; Xin Wang 035; Ying Wang 009 (Inf. Sci., 2023)

PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. - Hengrui Gu 002; Kaixiong Zhou; Xiaotian Han; Ninghao Liu; Ruobing Wang 003; Xin Wang 035 (ACL (1), 2024)

Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models. - Yingji Li; Mengnan Du; Rui Song 008; Xin Wang 035; Ying Wang 009 (ACL (Findings), 2024)

Molecular Data Programming: Towards Molecule Pseudo-labeling with Systematic Weak Supervision. - Xin Juan; Kaixiong Zhou; Ninghao Liu; Tianlong Chen 001; Xin Wang 035 (CVPR, 2024)

Pioneering Reliable Assessment in Text-to-Image Knowledge Editing: Leveraging a Fine-Grained Dataset and an Innovative Criterion. - Hengrui Gu 002; Kaixiong Zhou; Yili Wang 004; Ruobing Wang 003; Xin Wang 035 (EMNLP (Findings), 2024)

Mitigate Extrinsic Social Bias in Pre-trained Language Models via Continuous Prompts Adjustment. - Yiwei Dai; Hengrui Gu 002; Ying Wang 009; Xin Wang 035 (EMNLP, 2024)

LGCRS: LLM-Guided Representation-Enhancing for Conversational Recommender System. - Ruobing Wang 003; Xin He 003; Hengrui Gu 002; Xin Wang 035 (ICANN (9), 2024)

Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. - Yili Wang 004; Kaixiong Zhou; Ninghao Liu; Ying Wang 009; Xin Wang 035 (ICLR, 2024)

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. - Rui Miao 003; Kaixiong Zhou; Yili Wang 004; Ninghao Liu; Ying Wang 009; Xin Wang 035 (ICML, 2024)

Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models. - Xu Shen 002; Yili Wang 004; Kaixiong Zhou; Shirui Pan; Xin Wang 035 (KDD, 2024)

Mitigating social biases of pre-trained language models via contrastive self-debiasing with double data augmentation. - Yingji Li; Mengnan Du; Rui Song 008; Xin Wang 035; Mingchen Sun; Ying Wang 009 (Artif. Intell., 2024)

Adaptive Self-supervised Learning for Social Recommendations. - Xin He 003; Shanru Lin; Wenqi Fan; Mingchen Sun; Ying Wang 009; Xin Wang 035 (CoRR, 2024)

Multi-strategy adaptive data augmentation for Graph Neural Networks. - Xin Juan; Xiao Liang; Haotian Xue 001; Xin Wang 035 (Expert Syst. Appl., 2024)

A two-stage co-adversarial perturbation to mitigate out-of-distribution generalization of large-scale graph. - Yili Wang 004; Haotian Xue 001; Xin Wang 035 (Expert Syst. Appl., 2024)

GPL-GNN: Graph prompt learning for graph neural network. - Zihao Chen; Ying Wang 009; Fuyuan Ma; Hao Yuan; Xin Wang 035 (Knowl. Based Syst., 2024)

Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks. - Ying Wang 009; Yingji Li; Yue Wu; Xin Wang 035 (Expert Syst. Appl., 2024)

Towards Domain-Aware Stable Meta Learning for Out-of-Distribution Generalization. - Mingchen Sun; Yingji Li; Ying Wang 009; Xin Wang 035 (ACM Trans. Knowl. Discov. Data, 2024)

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark. - Yili Wang 004; Yixin Liu 001; Xu Shen 002; Chenyu Li; Rui Miao 003; Kaize Ding; Ying Wang 009; Shirui Pan; Xin Wang 035 (ICLR, 2025)

Dynamic self-training with less uncertainty for graph imbalance learning. - Xin Juan; Meixin Peng; Xin Wang 035 (Expert Syst. Appl., 2025)

Balancing user preferences by social networks: A condition-guided social recommendation model for mitigating popularity bias. - Xin He 003; Wenqi Fan; Ruobing Wang 003; Yili Wang 004; Ying Wang 009; Shirui Pan; Xin Wang 035 (Neural Networks, 2025)

Graph Defense Diffusion Model. - Xin He 003; Wenqi Fan; Yili Wang 004; Chengyi Liu; Rui Miao 003; Xin Juan; Xin Wang 035 (CoRR, 2025)

Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space. - Xin He 003; Yili Wang 004; Wenqi Fan; Xu Shen 002; Xin Juan; Rui Miao 003; Xin Wang 035 (CoRR, 2025)

Raising the Bar in Graph OOD Generalization: Invariant Learning Beyond Explicit Environment Modeling. - Xu Shen 002; Yixin Liu 001; Yili Wang 004; Rui Miao 003; Yiwei Dai; Shirui Pan; Xin Wang 035 (CoRR, 2025)

Latte: Transfering LLMs' Latent-level Knowledge for Few-shot Tabular Learning. - Ruxue Shi; Hengrui Gu 002; Hangting Ye; Yiwei Dai; Xu Shen 002; Xin Wang 035 (CoRR, 2025)

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification. - Ruxue Shi; Hengrui Gu 002; Xu Shen 002; Xin Wang 035 (CoRR, 2025)

Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems. - Xu Shen 002; Yixin Liu 001; Yiwei Dai; Yili Wang 004; Rui Miao 003; Yue Tan; Shirui Pan; Xin Wang 035 (CoRR, 2025)

BlindGuard: Safeguarding LLM-based Multi-Agent Systems under Unknown Attacks. - Rui Miao 003; Yixin Liu 001; Yili Wang 004; Xu Shen 002; Yue Tan; Yiwei Dai; Shirui Pan; Xin Wang 035 (CoRR, 2025)

AdaGCL+: An Adaptive Subgraph Contrastive Learning Toward Tackling Topological Bias. - Yili Wang 004; Yaohua Liu; Ninghao Liu; Rui Miao 003; Ying Wang 009; Xin Wang 035 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)