Selected Publications

Please check the Google Scholar for the full list.

  1. [1]
    Scalable Intelligence under Limited Supervision: Principles, Structures, and Adaptive Agents.
    Z. Song, Y. Wang and Q. Yao.
    International Joint Conference on Artificial Intelligence (IJCAI), Tutorial Track, 2026.
  2. [2]
    PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction.
    Z. Meng, Q. Wang, Z. Dou, Z. Song, Z. Zhou, I. King and P. Zhao.
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  3. [3]
    Semi-supervised Instruction Tuning for Large Language Models on Text-Attributed Graphs.
    Z. Song and I. King.
    Companion Proceedings of the ACM Web Conference (TheWebConf), 2026.
  4. [4]
    M2PG: MoE-based Adaptive Multi-Perspective Graph Fusion for Protein Representation Learning.
    Y. Wang, J. Shen, Z. Wu, Y. Xu, S. Tan, M. Xu, C. Wang, Z. Song and P. Tiwari.
    AAAI Conference on Artificial Intelligence (AAAI), 2026. Oral
  5. [5]
    Track and Tweak: Monitoring and Improving Group Fairness for Temporal Graph Neural Networks in Real Time.
    Z. Song, M. Li, Y. Zhang, I. King and J. M. Hernández-Lobato.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
  6. [6]
    Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space.
    Z. Song, Z. Meng and J. M. Hernández-Lobato.
    International Conference on Machine Learning (ICML), 2025.
  7. [7]
    Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification.
    L. Liang, F. Bu, Z. Song, Z. Xu, S. Pan and K. Shin.
    International Conference on Machine Learning (ICML), 2025.
  8. [8]
    FedEDM: Federated Equivariant Diffusion Model for 3D Molecule Generation with Enhanced Communication Efficiency.
    Z. Song, I. King and J. M. Hernández-Lobato.
    Companion Proceedings of the ACM Web Conference (TheWebConf), 2025.
  9. [9]
    Context-aware Inductive Knowledge Graph Completion with Latent Type and Subgraph Reasoning.
    M. Li, C. Yang, C. Xu, Z. Song, X. Jiang, J. Guo, H. Leung and I. King.
    AAAI Conference on Artificial Intelligence (AAAI), 2025.
  10. [10]
    Geometric View of Soft Decorrelation in Self-Supervised Learning.
    Y. Zhang, H. Zhu, Z. Song, Y. Chen, X. Fu, P. Koniusz and I. King.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
  11. [11]
    A Systematic Survey on Federated Semi-supervised Learning.
    Z. Song, X. Yang, Y. Zhang, X. Fu, Z. Xu and I. King.
    International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  12. [12]
    Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations.
    Z. Meng, L. Zeng, Z. Song, T. Xu, P. Zhao and I. King.
    International Joint Conference on Artificial Intelligence (IJCAI), 2024.
  13. [13]
    A Diffusion-based Pre-training Framework for Crystal Property Prediction.
    Z. Song, Z. Meng and I. King.
    AAAI Conference on Artificial Intelligence (AAAI), 2024. Oral
  14. [14]
    Tackling Long-tailed Distribution Issue in Graph Neural Networks via Normalization.
    L. Liang, Z. Xu, Z. Song, I. King, Y. Qi and J. Ye.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
  15. [15]
    Mitigating the Popularity Bias in Graph-based Collaborative Filtering.
    Y. Zhang, H. Zhu, Y. Chen, Z. Song, P. Koniusz and I. King.
    Conference on Neural Information Processing Systems (NeurIPS), 2023. Spotlight
  16. [16]
    No Change, No Gain: Empowering Graph Neural Networks with Expected Model Change Maximization for Active Learning.
    Z. Song, Y. Zhang and I. King.
    Conference on Neural Information Processing Systems (NeurIPS), 2023. Spotlight
  17. [17]
    Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning.
    Z. Song, Y. Zhang and I. King.
    Conference on Neural Information Processing Systems (NeurIPS), 2023.
  18. [18]
    Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily.
    L. Liang, X. Hu, Z. Xu, Z. Song and I. King.
    Conference on Neural Information Processing Systems (NeurIPS), 2023.
  19. [19]
    Towards Fair Financial Services for All: A Temporal GNN Approach for Individual Fairness on Transaction Networks.
    Z. Song, Y. Zhang and I. King.
    ACM International Conference on Information and Knowledge Management (CIKM), 2023.
  20. [20]
    Contrastive Cross-scale Graph Knowledge Synergy.
    Y. Zhang, Y. Chen, Z. Song and I. King.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.
  21. [21]
    WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering.
    Y. Chen, Y. Zhang, M. Yang, Z. Song, C. Ma and I. King.
    International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023.
  22. [22]
    Graph Component Contrastive Learning for Concept Relatedness Estimation.
    Y. Ma, Z. Song, X. Hu, J. Li, Y. Zhang and I. King.
    AAAI Conference on Artificial Intelligence (AAAI), 2023.
  23. [23]
    SFA: Spectral Feature Augmentation for Graph Contrastive Learning.
    Y. Zhang, H. Zhu, Z. Song, P. Koniusz and I. King.
    AAAI Conference on Artificial Intelligence (AAAI), 2023.
  24. [24]
    A Survey on Deep Semi-supervised Learning.
    X. Yang, Z. Song, I. King and Z. Xu.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
  25. [25]
    Graph-based Semi-supervised Learning: A Comprehensive Review.
    Z. Song, X. Yang, Z. Xu and I. King.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
  26. [26]
    COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning.
    Y. Zhang, H. Zhu, Z. Song, P. Koniusz and I. King.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
  27. [27]
    Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification.
    Z. Song, Y. Zhang and I. King.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
  28. [28]
    Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization.
    Z. Song and I. King.
    AAAI Conference on Artificial Intelligence (AAAI), 2022.
  29. [29]
    Semi-supervised Multi-label Learning for Graph-structured Data.
    Z. Song, Z. Meng, Y. Zhang and I. King.
    ACM International Conference on Information and Knowledge Management (CIKM), 2021.