Publications

You can also find my articles in my Google Scholar and DBLP.

2024

• Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations.
  Qingqing Long, Zheng Fang, Chen Fang, Chong Chen, Yuanchun Zhou.
  In The Web Conference (TheWebConf, a.k.a. WWW), 2024.

• Inductive Graph Alignment Prompt: Bridging the Gap between Graph Pre-training and Inductive Fine-tuning From Spectral Perspective.
  Yuchen Yan, Peiyan Zhang, Zheng Fang, Qingqing Long (Corresponding Author).
  In The Web Conference (TheWebConf, a.k.a. WWW), 2024.

• A Survey of Data-efficient Graph Learning.
  Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Junyu Luo, Zhiping Xiao, Ming Zhang.
  In International Joint Conference on Artificial Intelligence (IJCAI), 2024.

• MOAT: Graph Prompting for 3D Molecular Graphs.
  Qingqing Long, Yuchen Yan, Wentao Cui, Wei Ju, Zhihong Zhu, Yuanchun Zhou, Xuezhi Wang, Meng Xiao.
  In The 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• Refining computational inference of gene regulatory networks: integrating knockout data within a multi-task framework.
  Wentao Cui, Qingqing Long, Meng Xiao, Xuezhi Wang, Guihai Feng, Xin Li, Yuanchun Zhou.
  In Briefings in Bioinformatics (BIB), 2024.

• PIXEL: Prompt-based Zero-shot Hashing via Visual and Textual Semantic Alignment.
  Zeyu Dong, Qingqing Long, Yihang Zhou, Xiao Luo, Zhihong Zhu, Yidong Wang, Pengyang Wang, Yuanchun Zhou.
  In The 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• Learning Knowledge-diverse Experts for Long-tailed Graph Classification.
  Zengyang Mao, Wei Ju, Siyu Yi, Yifan Wang, Qingqing Long, Nan Yin, Xinwang Liu, Ming Zhang.
  In Transactions on Knowledge Discovery from Data (TKDD), 2024.

• GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation.
  Guojiao Lin, Zhen Meng, Dongjie Wang, Qingqing Long, Yuanchun Zhou, Meng Xiao.
  In The 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.

• A comprehensive survey on deep graph representation learning.
  Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang.
  In Neural Networks, 2024.

• Multivariate Cooperative Game for Image-Report Pairs: Hierarchical Semantic Alignment for Medical Report Generation.
  Zhihong Zhu, Xuxin Cheng, Yunyan Zhang, Zhaorun Chen, Qingqing Long, Hongxiang Li, Zhiqi Huang, Xian Wu, Yefeng Zheng.
  In The 27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024.

• Comprehensive Metapath-based Heterogeneous Graph Transformer for Gene-Disease Association Prediction.
  Wentao Cui, Shoubo Li, Chen Fang, Qingqing Long, Chenrui Wang, Xuezhi Wang, and Yuanchun Zhou.
  In IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 2024.

• How do Large Language Models understand Genes and Cells.
  Chen Fang, Yidong Wang, Yunze Song, Qingqing Long, Wang Lu, Linghui Chen, Guihai Feng, Yuanchun Zhou, Xin Li.
  In ACM Transactions on Intelligent Systems and Technology (TIST), 2024.

• AMPCL: Adaptive Meta-Path Selection and Contrastive Learning for miRNA-Disease Prediction.
  Wentao Cui, Chuan Hu, Chen Fang, Qingqing Long, Jiahao Zhang, Xuezhi Wang, Yuanchun Zhou.
  In 31st International Conference on Neural Information Processing (ICNOIP), 2024.

2022

• Polarized Graph Neural Networks
  Zheng Fang, Lingjun Xu, Guojie Song, Qingqing Long, Yingxue Zhang.
  In The Web Conference (TheWebConf, a.k.a. WWW), 2022

• Joint Optimization of Ad Ranking and Creative Selection
  Kaiyi Lin, Xiang Zhang, Pengjie Wang, Qingqing Long, Hongbo Deng, Jian Xu, Bo Zheng. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022

• Deep Convolutional Neural Network based Medical Concept Normalization [pdf]
  Guojie Song, Qingqing Long, Yi Luo, Yiming Wang, Yilun Jin.
  In IEEE Transactions on Big Data, 2022.

2021

• HGK-GNN: Heterogeneous Graph Kernel based Graph Neural Networks [pdf]
  Qingqing Long, Lingjun Xu, Zheng Fang, Guojie Song.
  In The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021

• Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels [pdf][code]
  Qingqing Long, Yilun Jin, Yi Wu, Guojie Song.
  In The Web Conference (TheWebConf, a.k.a. WWW), 2021.

• Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting [pdf]
  Zheng Fang, Qingqing Long, Guojie Song, Kunqing Xie.
  In The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021

• Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction [pdf]
  Feng Li, Bencheng Yan, Qingqing Long, Pengjie Wang, Wei Lin, Jian Xu, Bo Zheng.
  In The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021

2020

• Graph Structural-topic Neural Network [pdf][code][slides]
  Qingqing Long, Yilun Jin, Guojie Song, Yi Li, Wei Lin.
  In The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020

• Learning Node Representations from Noisy Graph Structures
  Junshan Wang, Ziyao Li, Qingqing Long, Weiyu Zhang, Guojie Song, Chuan Shi.
  In * IEEE International Conference on Data Mining (ICDM)*, 2020

2019

• Hierarchical Community Structure Preserving Network Embedding: A Subspace Approach [pdf][code]
  Qingqing Long, Yiming Wang, Lun Du, Guojie Song, Yilun Jin, Wei Lin.
  In The 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019. Best Research Paper Runner-up Award.