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期刊文章:

[1] Huawei Shen, Yuanhao Liu, Kaike Zhang, Qi Cao, Xueqi Cheng. The Rising Safety Concerns of Deep Recommender Systems. The Innovation. 2025. (IF: 25.7)

[2] Kaike?Zhang, Qi Cao, Fei Sun, Yunfan Wu, Shuchang Tao, Huawei Shen, Xueqi Cheng. Robust Recommender System: A Survey and Future Directions. ACM Computing Surveys. 2025. (IF: 28.0)

[3] Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Liang Hou, Xueqi Cheng. Graph Adversarial Immunization for Certifiable Robustness. IEEE Transactions on Knowledge and Data Engineering. 2024, 36(4): 1597-1610.

[4] Keting Cen, Huawei Shen, Qi Cao, Bingbing Xu, Xueqi Cheng. Identity-Preserving Adversarial Training for Robust Network Embedding. Journal of Computer Science and Technology. 2024, 39(1): 177-191.

[5] Shuchang Tao, Qi Cao, Huawei Shen, Yunfan Wu, Bingbing Xu, Xueqi Cheng. IDEA: Invariant Defense for Graph Adversarial Robustness. Information Sciences. 2024, 680: 121171.

[6] Yige Yuan, Bingbing Xu, Huawei Shen, Qi Cao, Keting Cen, Wen Zheng, Xueqi Cheng. Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective. Neural Networks. 2024, 172: 106125.

[7] Junjie Huang, Ruobing Xie, Qi Cao, Huawei Shen, Shaoliang Zhang, Feng Xia, Xueqi Cheng. Negative Can Be Positive: Signed Graph Neural Networks for Recommendation. Information Processing & Management. 2023, 60(4): 103403.

[8] Shuchang?Tao, Qi Cao, Huawei Shen, Yunfan Wu, Liang Hou, Fei Sun, Xueqi Cheng. Adversarial Camouflage for Node Injection Attack on Graphs.?Information Sciences. 2023, 649: 119611.

[9] Zhaohui Wang, Qi Cao, Huawei Shen, Bingbing Xu, Keting Cen, Xueqi Cheng. Location-aware Convolutional Neural Networks for Graph Classification. Neural Networks. 2022, 155: 74-83.

[10] Qi Cao, Huawei Shen, Jinhua Gao, Xueqi Cheng. Learning Diffusion Model-free and Efficient Influence Function for Influence Maximization from Information Cascades. Knowledge and Information Systems. 2021, 63(5): 1173-1196.

[11] 曹婍, 沈華偉, 高金華, 程學(xué)旗. 基于深度學(xué)習(xí)的流行度預(yù)測(cè)研究. 中文信息學(xué)報(bào). 2021, 35(2): 1-18.

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會(huì)議文章：

[1] Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen, Xueqi Cheng. Personalized Denoising Implicit Feedback for Robust Recommender System. In Proceedings of the ACM on Web Conference (WebConf 2025).

[2] Kaike Zhang, Yunfan Wu, Yougang Lyu, Du Su, Yingqiang Ge, Shuchang Liu, Qi Cao, Zhaochun Ren, Fei Sun. The 1st Workshop on Human-Centered Recommender Systems. In Companion Proceedings of the ACM on Web Conference (WebConf 2025).

[3] Yuanhao Liu, Qi Cao, Huawei Shen, Kaike Zhang, Yunfan Wu, Xueqi Cheng. "I Know You Are Discriminatory!": Automated Substantiating for Individual Fairness Auditing of AI Systems. In Proceedings of the 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW 2025).

[4] Wanli Yang, Fei Sun, Jiajun Tan, Xinyu Ma, Qi Cao, Dawei Yin, Huawei Shen, Xueqi Cheng. The Mirage of Model Editing: Revisiting Evaluation in the Wild. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025).

[5] Beining Huang, Du Su, Fei Sun, Qi Cao, Huawei Shen, Xueqi Cheng. Low-Entropy Watermark Detection via Bayes’ Rule Derived Detector. In Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL Findings 2025).

[6] Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen, Xueqi Cheng. Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation. In Proceedings of the 38th International Conference on Neural Information Processing Systems (NeurIPS 2024).

[7] Yu Chen, Qi Cao, Kaike Zhang, Xuchao Liu, Huawei Shen. PKAD: Pretrained Knowledge is All You Need to Detect and Mitigate Textual Backdoor Attacks. In Findings of the Association for Computational Linguistics: EMNLP 2024 (EMNLP Findings 2024).

[8] Yunfan Wu, Qi Cao, Shuchang Tao, Kaike Zhang, Fei Sun, Huawei Shen. Accelerating the Surrogate Retraining for Poisoning Attacks against Recommender Systems. In Proceedings of the 18th ACM Conference on Recommender Systems (RecSys 2024).

[9] Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen, Xueqi Cheng. Improving the Shortest Plank: Vulnerability-aware Adversarial Training for Robust Recommender System. In Proceedings of the 18th ACM Conference on Recommender Systems (RecSys 2024).

[10] Hexiang Tan, Fei Sun, Wanli Yang, Yuanzhuo Wang, Qi Cao, Xueqi Cheng. Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts?. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

[11] Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding. When to Trust LLMs: Aligning Confidence with Response Quality. In Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL Findings 2024).

[12] Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun, Huawei Shen, Xueqi Cheng. Lorec: Combating poisons with large language model for robust sequential recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024).

[13] Wen Zheng, Bingbing Xu, Emiao Lu, Yang Li, Qi Cao, Xuan Zong, Huawei Shen. MIDLG: Mutual information based dual level GNN for transaction fraud complaint verification. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).

[14] Kaike Zhang, Qi Cao, Gaolin Fang, Bingbing Xu, Hongjian Zou, Huawei Shen, Xueqi Cheng. Dyted: Disentangled representation learning for discrete-time dynamic graph. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).

[15] Yuanhao Liu, Qi Cao, Huawei Shen, Yunfan Wu, Shuchang Tao, Xueqi Cheng. Popularity debiasing from exposure to interaction in collaborative filtering. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023).

[16] Junjie Huang, Qi Cao, Ruobing Xie, Shaoliang Zhang, Feng Xia, Huawei Shen, Xueqi Cheng. Adversarial learning data augmentation for graph contrastive learning in recommendation. In Proceedings of the International Conference on Database Systems for Advanced Applications (DASFAA 2023).

[17]?Qi Cao, Huawei Shen, Jinhua Gao, Xueqi Cheng. PREP: Pre-training with Temporal Elapse Inference for Popularity Prediction. In Companion Proceedings of the 31st ACM Web Conference (WebConf 2022).

[18] Yunfan Wu, Qi Cao, Huawei Shen, Shuchang Tao, Xueqi Cheng. INMO: A Model-Agnostic and Scalable Module for Inductive Collaborative Filtering. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022).

[19] Keting Cen, Huawei Shen, Qi Cao, Bingbing Xu, Xueqi Cheng. Towards Powerful Graph Contrastive Learning without Negative Examples. In Proceedings of the 2022 International Joint Conference on Neural Networks (IJCNN 2022).

[20] Shuchang Tao, Qi Cao, Huawei Shen, Junjie Huang, Yunfan Wu, Xueqi Cheng. Single Node Injection Attack against Graph Neural Networks. Proceedings of the 30th International Conference on Information and Knowledge Management (CIKM 2021).

[21] Liang Hou, Huawei Shen, Qi Cao, Xueqi Cheng. Self-Supervised GANs with Label Augmentation. In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS 2021).

[22] Shuchang Tao, Huawei Shen, Qi Cao, Liang Hou, Xueqi Cheng. Adversarial Immunization for Certifiable Robustness on Graphs. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021).

[23] Junjie Huang, Huawei Shen, Qi Cao, Shuchang Tao, Xueqi Cheng. Signed Bipartite Graph Neural Networks. In Proceedings of the 30th International Conference on Information and Knowledge Management (CIKM 2021).

[24] Junjie Huang, Huawei Shen, Qi Cao, Cai Li, Xueqi Cheng. How Medical Crowdfunding Helps People? A Large-scale Case Study on Waterdrop Fundraising. In Proceedings of the 15th International AAAI Conference on Web and Social Media (ICWSM 2021).

[25] Bingbing Xu, Huawei Shen, Bingjie Sun, Rong An, Qi Cao, Xueqi Cheng. Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021).

[26] Qi Cao, Huawei Shen, Jinhua Gao, Bingzheng Wei, Xueqi Cheng. Popularity Prediction on Social Platforms with Coupled Graph Neural Networks. In Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM 2020).

[27] Rong Yan, Huawei Shen, Qi Cao, Keting Cen, Li Wang. GraphWGAN: Graph Representation Learning with Wasserstein Generative Adversarial Networks. In Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing (BigComp 2020, Best Paper Award).

[28] Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng. Graph Wavelet Neural Network. In Proceedings of the International Conference on Learning Representation (ICLR 2019).

[29] Bingbing Xu, Huawei Shen, Qi Cao, Keting Cen, Xueqi Cheng. Graph Convolutional Neural Networks using Heat Kernel for Semi-supervised Learning. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019).

[30] Qi Cao, Huawei Shen, Keting Cen, Wentao Ouyang, Xueqi Cheng. DeepHawkes: Bridging the Gap between Prediction and Understanding of Information Cascades. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (CIKM 2017).

[31] Qi Cao, Huawei Shen, Hao Gao, Jinhua Gao, Xueqi Cheng. Predicting the Popularity of Online Content with Group-specific Models. In Companion Proceedings of the 26th International Conference on World Wide Web (WWW 2017).

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專利：

[1] 程學(xué)旗, 曹婍, 沈華偉, 高金華, 劉盛華. 網(wǎng)絡(luò)信息傳播影響力度量方法、系統(tǒng)及影響力最大化方法.