01 2026
Exploring Test-time Scaling via Prediction Merging on Large-Scale Recommendation
Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR
Xing Tang
Associate Professor
School of Artificial Intelligence, Shenzhen Technology University
Xing Tang is an Associate Professor in the School of Artificial Intelligence at
Shenzhen Technology University (SZTU). He received his Ph.D. in Computer Science from
Xidian University in 2016 under the supervision of
Prof. Qiguang Miao. After graduation,
he joined Huawei Noah's Ark Lab, where
he worked with
Dr. Xiuqiang He
and Dr. Ruiming Tang.
He later spent time at Tencent ARC Lab,
working with
Dr. Ying Shan.
His current research focuses on recommender systems and personalized large language
models (LLMs), with three closely related directions: recommendation modeling,
personalized LLM agents, and applications of these technologies in finance.
Recommender SystemsPersonalized LLMsAI for Finance
I welcome visiting researchers and research collaborations. Please contact me if you are interested.
01
News
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I will serve as a PC member for WSDM 2027 and DASFAA 2027.
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I will serve as an Area Chair for ICLR 2027.
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One paper on multi-behavior sequential recommendation was accepted by WISE 2026, and one paper on test-time methods for sequential recommendation was accepted by CIKM 2026.
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I will serve as an Area Chair for the KDD 2027 Research and ADS tracks (First Cycle).
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One paper on tool selection was accepted by ACM MM 2026.
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One paper on LLMs for non-overlapping cross-domain CTR prediction was accepted by RecSys 2026.
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I will serve as a PC member for AAAI 2027, ACL ARR (May), and the KDD 2027 D&B track.
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Two papers on LLMs for financial QA and multimodal CTR were accepted by the KDD 2026 ADS track (February Cycle).
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One paper on context compression for RAG was accepted by ICML 2026.
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I will serve as a PC member for ICDM 2026.
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- 02 2026
Data-Driven Function Calling Improvements in Large Language Model for Online Financial QA
Proceedings of the ACM Web Conference 2026,WebConf
- 03 2025
Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation
39th Annual Conference on Neural Information Processing Systems, NeurIPS
- 04 2025
Retrieval Augmented Cross-Domain LifeLong Behavior Modeling for Enhancing Click-through Rate Prediction
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD
- 05 2025
Timing is Important: Risk-Aware Fund Allocation Based on Time-Series Forecasting
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD
- 06 2025
Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
42nd International Conference on Machine Learning, ICML
- 07 2024
OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM
- 08 2024
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
Proceedings of the 18th ACM Conference on Recommender Systems, RecSys
- 09 2023
Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
37th Annual Conference on Neural Information Processing Systems, NeurIPS
- 10 2023
Optimizing Feature Set for Click-Through Rate Prediction
Proceedings of the ACM Web Conference 2023, WebConf
03
Service
Conferences
Senior Area Chair / Area Chair
- KDD 2025, 2026, 2027
- ICLR 2026, 2027
- NeurIPS 2026
- ICASSP 2026
Conferences
Program Committee Member
- Data Mining
- KDD (2019–2025), ICDM (2025–), ECML-PKDD (2024–), DASFAA (2027)
- Information Retrieval
- SIGIR (2025–), WebConf (2024–), RecSys (2024–), WSDM (2024–), CIKM (2023–)
- Machine Learning
- NeurIPS (2024–2025), ICML (2024–), ICLR (2025), AISTATS (2025–)
- Artificial Intelligence
- AAAI (2024–), IJCAI (2024–), ACM MM (2025–), ACL ARR (2026)
Journal Reviewer 11 journals
- IEEE Transactions on Knowledge and Data Engineering (TKDE)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
- ACM Transactions on Information Systems (TOIS)
- ACM Transactions on Recommender Systems (TORS)
- Neural Networks (NeuNet)
- Pattern Recognition (PR)
- Knowledge-Based Systems (KNOSYS)
- Engineering Applications of Artificial Intelligence (EAAI)
- Expert Systems with Applications (ESWA)
- Neurocomputing (NeuCom)
- Computers & Security (COSE)
04
Group
Intelligent Information and Decision Lab (I.I.D Lab)
Faculty
- Prof. Lingjie Li
Ph.D. Students
- Yuhao Wu
co-supervised with Prof. Dugang Liu; WISE 2026
Master's Students
- Zhentai Chen
co-supervised with Prof. Jingyan Jiang; internship at Ant Group; SIGIR 2026
- Jun Zhang
co-supervised with Prof. Dugang Liu; internship at JD.com; SIGIR 2026
Undergraduate Students
- Jingyang Bin
RecSys 2026, CIKM 2026, KDD 2026
- Hanchong Chen
master's student at PolyU in Hong Kong
- Zhuanglin Chen
- Xiongfeng Shan
Off-Campus Collaborators
- Prof. Dugang Liu
Shenzhen University
- Dr. Fuyuan Lyu
Vatic Labs
- Dr. Shiwei Li
Tongyi Lab
- Dr. Ziqiang Cui
City University of Hong Kong
- Dr. Zexu Sun
JD Explore Academy
05
Teaching
- 01
Fundamentals of Programming Languages
- 02
Python Programming
- 03
Machine Learning System