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 focus on large language model and recommendation. His research interests mainly focus on advancing recommendation models, developing LLM agent with tool and memory, investigating financial time series.

Research interest:

  • Recommendation Models
  • Large Language Model
  • Financial Time Series

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

News

Oct 24, 2025 One paper about multi-scenario multi-task recommendation is accepted by WSDM 2026.
Sep 19, 2025 Two papers about LLM finetuning and Sequential Recommendation are accepted by Neurips 2025.
Aug 22, 2025 I will serve as PC member for AISTATS 2026 and ECIR 2026.
Aug 15, 2025 I will serve as PC member for WebConf Industry Track and Recsys Track 2026.
Aug 03, 2025 I will serve as SAC for KDD 2026 ADS track, PC member for KDD 2026 Research track, Datasets and Benchmarks Track(Febrary Cycle).
Jul 13, 2025 I will serve as PC member for AAAI 2026.
Jun 19, 2025 I will serve as PC member for WSDM 2026.
May 30, 2025 I will serve as PC member for ICDM 2025.

Selected Publications

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

  1. 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
  2. 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
  3. 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
  4. 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
  5. Conference
    Comprehending Knowledge Graphs with Large Language Models for Recommender Systems
    Ziqiang Cui, Yunpeng Weng, Xing Tang#, Fuyuan Lyu, Dugang Liu, Xiuqiang He, and Chen Ma#
    In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2025
  6. 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
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  7. 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
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  8. Conference
    FedBAT: Communication-efficient Federated Learning via Learnable Binarization
    Shiwei Li, Wenchao Xu, Haozhao Wang#, Xing Tang#, Yining Qi, Shijie Xu, Weihong Luo, Yuhua Li, Xiuqiang He, and Ruixuan Li#
    In 41st International Conference on Machine Learning, ICML, 2024
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  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
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  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
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  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
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  12. Conference
    DIWIFT: Discovering Instance-wise Influential Features for Tabular Data
    Dugang Liu*, Pengxiang Cheng*, Hong Zhu*, Xing Tang*, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, and Xiuqiang He
    In Proceedings of the ACM Web Conference 2023, WebConf, 2023
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  13. 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
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