| 2026 | ACL | Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning. | Yuhang Wu, Xiangqing Shen, Fanfan Wang, Cangqi Zhou, Zhen Wu, Xinyu Dai, Rui Xia |
| 2024 | ICWS | Timeliness-Selective Incentive Federated Crowdsourcing. | Xiaoqian Jiang, Haiyang Diao, Cangqi Zhou, Jing Zhang |
| 2023 | APWEB | Heterogeneous Graph Contrastive Learning with Dual Aggregation Scheme and Adaptive Augmentation. | Yingjie Xie, Qi Yan, Cangqi Zhou, Jing Zhang, Dianming Hu |
| 2023 | ICANN | Multi-Granularity Contrastive Learning for Graph with Hierarchical Pooling. | Peishuo Liu, Cangqi Zhou, Xiao Liu, Jing Zhang, Qianmu Li |
| 2023 | ICDM | Hierarchical Graph Contrastive Learning via Debiasing Noise Samples with Adaptive Repelling Ratio. | Peishuo Liu, Cangqi Zhou, Jing Zhang, Qianmu Li, Dianming Hu |
| 2022 | CIKM | End-to-end Modularity-based Community Co-partition in Bipartite Networks. | Cangqi Zhou, Yuxiang Wang, Jing Zhang, Jiqiong Jiang, Dianming Hu |
| 2022 | IJCNN | Attributed Graph Clustering with Double Contrastive Projector. | Yuxiang Wang, Cangqi Zhou, Jing Zhang, Qianmu Li |
| 2022 | PAKDD | Neural Topic Modeling with Gaussian Mixture Model and Householder Flow. | Cangqi Zhou, Sunyue Xu, Hao Ban, Jing Zhang |
| 2022 | WSDM | AngHNE: Representation Learning for Bipartite Heterogeneous Networks with Angular Loss. | Cangqi Zhou, Hui Chen, Jing Zhang, Qianmu Li, Dianming Hu |
| 2021 | ICDM | Topic-Attentive Encoder-Decoder with Pre-Trained Language Model for Keyphrase Generation. | Cangqi Zhou, Jinling Shang, Jing Zhang, Qianmu Li, Dianming Hu |
| 2021 | IJCNN | Heterogeneous Graph Embedding Based on Edge-aware Neighborhood Convolution. | Hui Chen, Cangqi Zhou, Jing Zhang, Qianmu Li |
| 2019 | WISE | Semi-supervised Graph Embedding for Multi-label Graph Node Classification. | Kaisheng Gao, Jing Zhang, Cangqi Zhou |