Xin Wang

Orcid: 0000-0001-9448-7689

Affiliations:
  • Jilin University (JLU), School of Artificial Intelligence, Changchun, China
  • Changchun Institute of Technology (CIT), School of Computer Technology and Engineering, China
  • Jilin University, College of Computer Science and Technology, Changchun, China (PhD 2015)
  • Ministry of Education, Key Laboratory of Symbolic Computation and Knowledge Engineering, Changchun, China
  • Guilin University of Electronic Technology, Guangxi Key Laboratory of Trusted Software, China


According to our database1, Xin Wang authored at least 46 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Exploring Multiple Hypergraphs for Heterogeneous Graph Neural Networks.
Expert Syst. Appl., February, 2024

GPL-GNN: Graph prompt learning for graph neural network.
Knowl. Based Syst., 2024

A two-stage co-adversarial perturbation to mitigate out-of-distribution generalization of large-scale graph.
Expert Syst. Appl., 2024

Multi-strategy adaptive data augmentation for Graph Neural Networks.
Expert Syst. Appl., 2024

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark.
CoRR, 2024

Balancing User Preferences by Social Networks: A Condition-Guided Social Recommendation Model for Mitigating Popularity Bias.
CoRR, 2024

Mitigating social biases of pre-trained language models via contrastive self-debiasing with double data augmentation.
Artif. Intell., 2024

Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Data-Centric Explainable Debiasing for Improving Fairness in Pre-trained Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

PokeMQA: Programmable knowledge editing for Multi-hop Question Answering.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Generating real-world hypergraphs via deep generative models.
Inf. Sci., November, 2023

Structural-aware motif-based prompt tuning for graph clustering.
Inf. Sci., November, 2023

INS-GNN: Improving graph imbalance learning with self-supervision.
Inf. Sci., August, 2023

A Survey on Fairness in Large Language Models.
CoRR, 2023

A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges.
CoRR, 2023

Clothes Grasping and Unfolding Based on RGB-D Semantic Segmentation.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

LAGCL: Towards Stable and Automated Graph Contrastive Learning.
Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Hierarchical recurrent neural networks for graph generation.
Inf. Sci., 2022

Negative samples selecting strategy for graph contrastive learning.
Inf. Sci., 2022

Contrastive Graph Convolutional Networks with adaptive augmentation for text classification.
Inf. Process. Manag., 2022

GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Towards Unified Representations of Knowledge Graph and Expert Rules for Machine Learning and Reasoning.
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, 2022

Cross-Domain Representation Learning for Clothes Unfolding in Robot-Assisted Dressing.
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Adversarial Training on Weights for Graph Neural Networks.
Proceedings of the 5th International Conference on Algorithms, 2022

AutoAUG : Automatic Data Augmentation for Graph Neural Networks.
Proceedings of the 5th International Conference on Algorithms, 2022

Orthogonal Graph Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Exploring graph capsual network for graph classification.
Inf. Sci., 2021

TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network.
Inf. Sci., 2021

CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks.
CoRR, 2021

Exploring Self-training for Imbalanced Node Classification.
Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020
Exploring Common and Label-Specific Features for Multi-Label Learning With Local Label Correlations.
IEEE Access, 2020

Traffic Flow Prediction via Spatial Temporal Graph Neural Network.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Attention-Guide Walk Model in Heterogeneous Information Network for Multi-Style Recommendation Explanation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Explanation Chains Model Based on the Fine-Grained Data.
Proceedings of the Natural Language Processing and Chinese Computing, 2019

2017
Building trust networks in the absence of trust relations.
Frontiers Inf. Technol. Electron. Eng., 2017

2016
Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust.
Comput. Intell. Neurosci., 2016

2015
Predicting Trust Relationships in Social Networks Based on WKNN.
J. Softw., 2015

Research on Trust Prediction from a Sociological Perspective.
J. Comput. Sci. Technol., 2015

Exploring Social Context for Topic Identification in Short and Noisy Texts.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Modeling Status Theory in Trust Prediction.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2012
Research on Web Query Translation based on Ontology.
J. Softw., 2012

2011
Research on discovering deep web entries.
Comput. Sci. Inf. Syst., 2011


  Loading...