Xing Tang

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Associate Professor, School of Artificial Intelligence, Shenzhen Technology University
xing.tang [at] hotmail.com, tangxing [at] sztu.edu.cn

Prof. Xing Tang is currently a Assoicate Professor at SZTU. He obtained his Ph.D. from Computer Science, Xidian University in 2016, under the supervision of Prof. Qiguang Miao. After graduation, He joined Huawei Noah’s Ark Lab, and worked with Dr.Xiuqiang He and Dr.Ruiming Tang. He also worked in Tencent ARC Lab with Dr.Ying Shan for a while. Now he focuses on recommendation systems and personalized large language models (LLMs), with his research interests mainly centered on three interrelated directions: advancing recommendation models, developing personalized LLM agents, and investigating the application of these technologies in finance.

Research interest:

  • Recommendation Models
  • Personalized LLMs
  • AI for Finance

Announcement: Interested in visiting or collaboration. You can contact me if you are interested!

News

Apr 03, 2026 Two papers about test-time scaling for large scale recommendation and semantic id for federated recommendation is accepted by SIGIR 2026.
Mar 24, 2026 I will serve as Area Chair for Neurips 2026 and PC for CIKM 2026.
Mar 14, 2026 I will serve as PC member for RecSys 2026.
Jan 28, 2026 I will serve as PC member for IJCAI 2026, ECML-PKDD 2026, and ACMMM 2026.
Jan 26, 2026 One paper about LoRA for finetuing is accepted by ICLR 2026.
Jan 24, 2026 I will serve as Area Chair for KDD 2026 Research, ADS track (Feburary Cycle), Reviewer for ECCV 2026 and ACL 2026.
Jan 14, 2026 One paper about Function calling for LLM is accepted by WebConf 2026.
Dec 20, 2025 I will serve as PC member for SIGIR 2026.

Selected Publications

* represents Co-first author and # represents Corresponding author.

  1. Conference
    Exploring Test-time Scaling via Prediction Merging on Large-Scale Recommendation
    Fuyuan Lyu, Zhentai Chen, Jingyan Jiang, Lingjie Li, Xing Tang#, Xiuqiang He, and Xue Liu
    In Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2026
  2. Conference
    Data-Driven Function Calling Improvements in Large Language Model for Online Financial QA
    Xing Tang, Hao Chen, Shiwei Li, Fuyuan Lyu, Weijie Shi, Lingjie Li, Dugang Liu, Xiku Du, Weihong Luo, and Xiuqiang He
    In Proceedings of the ACM Web Conference 2026,WebConf , 2026
    PDF
  3. Conference
    Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation
    Ziqiang Cui, Yunpeng Weng, Xing Tang#, Xiaokun Zhang, Shiwei Li, Peiyang Liu, Bowei He, Dugang Liu, Weihong Luo, Xiuqiang He, and Chen Ma#
    In 39th Annual Conference on Neural Information Processing Systems, NeurIPS, 2025
  4. Conference
    Retrieval Augmented Cross-Domain LifeLong Behavior Modeling for Enhancing Click-through Rate Prediction
    Xing Tang, Chaohua Yang*, Yuwen Fu*, Dongyang Ao, Shiwei Li, Fuyuan Lyu, Dugang Liu, and Xiuqiang He
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD , 2025
  5. Conference
    Timing is important: Risk-aware Fund Allocation based on Time-Series Forcasting
    Fuyuan Lyu, Linfeng Du, Yunpeng Weng, Qiufang Ying, Zhiyan Xu, Wen Zou, Haolun Wu, Xiuqiang He, and Xing Tang
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2025
  6. Conference
    Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
    Shiwei Li, Xiandi Luo, Xing Tang#, Haozhao Wang#, Hao Chen, Weihong Luo, Yuhua Li, Xiuqiang He, and Ruixuan Li#
    In 42nd International Conference on Machine Learning, ICML, 2025
  7. Conference
    OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
    Yunpeng Weng*, Xing Tang*, Zhenhao Xu, Fuyuan Lyu, Dugang Liu, Zexu Sun, and Xiuqiang He
    In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM , 2024
    HTML PDF
  8. Conference
    Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
    Xing Tang, Yang Qiao*, Fuyuan Lyu*, Dugang Liu, and Xiuqiang He
    In Proceedings of the 18th ACM Conference on Recommender Systems, RecSys, 2024
    HTML PDF
  9. Conference
    Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
    Fuyuan Lyu, Xing Tang#, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, Xiuqiang He, and Xue Liu
    In 37th Annual Conference on Neural Information Processing Systems, NeurIPS, 2023
    HTML PDF Code
  10. Conference
    OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction
    Xing Tang, Yang Qiao*, Yuwen Fu*, Fuyuan Lyu, Dugang Liu, and Xiuqiang He
    In European Conference on Machine Learning and Knowledge Discovery in Databases, ECML-PKDD, 2023
    HTML PDF
  11. Conference
    Explicit Feature Interaction-aware Uplift Network for Online Marketing
    Dugang Liu, Xing Tang#, Han Gao, Fuyuan Lyu, and Xiuqiang He#
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2023
    HTML PDF Code
  12. Conference
    Optimizing Feature Set for Click-Through Rate Prediction
    Fuyuan Lyu*, Xing Tang*, Dugang Liu, Liang Chen, Xiuqiang He, and Xue Liu
    In Proceedings of the ACM Web Conference 2023, WebConf, 2023
    HTML PDF Code