Publications

2025

  1. Journal
    Retrieval Augmented Cross-Domain LifeLong Behavior Modeling for Enhancing Click-through Rate Prediction
    Tang Xing, Yang* Chaohua, Fu* Yuwen, Ao Dongyang, Li Shiwei, Lyu Fuyuan, Liu Dugang, and He Xiuqiang
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD , 2025
  2. Conference
    Timing is important: Risk-aware Fund Allocation based on Time-Series Forcasting
    Lyu Fuyuan, Du Linfeng, Weng Yunpeng, Ying Qiufang, Xu Zhiyan, Zou Wen, Wu Haolun, He Xiuqiang, and Tang Xing
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2025
  3. Scenario Shared Instance Modeling for Click-through Rate Prediction
    Liu Dugang, Yang Chaohua, Fu Yuwen, Tang Xing, Li Gongfu, Lyu Fuyuan, He Xiuqiang, and Ming Zhong
    In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD , 2025
  4. Invariant Deep Uplift Modeling for Incentives Assignment in Online Marketing via Probability of Necessity and Sufficiency
    Sun Zexu, Han Qiyu, Yang Hao, Wu Anpeng, Zhu Minqin, Liu Dugang, Ma Chen, Weng Yunpeng, Tang Xing, and He# Xiuqiang
    In 42nd International Conference on Machine Learning, ICML, 2025
  5. Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics
    Li Shiwei, Luo Xiandi, Tang Xing, Wang# Haozhao, Chen Hao, Luo Weihong, Li Yuhua, He Xiuqiang, and Li# Ruixuan
    In 42nd International Conference on Machine Learning, ICML, 2025
  6. The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
    Li Shiwei, Luo Xiandi, Wang Haozhao, Tang Xing, Xu Shijie, Luo Weihong, Li Yuhua, He Xiuqiang, and Li Ruixuan
    In 42nd International Conference on Machine Learning, ICML, 2025
  7. Comprehending Knowledge Graphs with Large Language Models for Recommender Systems
    Cui Ziqiang, Weng Yunpeng, Tang Xing, Lyu Fuyuan, Liu Dugang, He Xiuqiang, and Ma# Chen
    In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2025
  8. Multi-scenario Instance Embedding Learning for Deep Recommneder Systems
    Yang Chaohua, Liu Dugang, Tang Xing, Fu Yuwen, He Xiuqiang, Zhao Xiangyu, and Zhong Ming
    In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2025
  9. A Predict-Then-Optimize Customer Allocation Framework for Online Fund Recommendation
    Tang Xing, Weng* Yunpeng, Lyu* Fuyuan, Liu Dugang, and He Xiuqiang
    In Database Systems for Advanced Applications - 30th International Conference, DASFAA , 2025
  10. Policy-aware Reward Modeling with Uncertainty-Gradient based Data Augmentation
    Sun Zexu, Guo Yiju, Lin Yankai, Chen Xu, Qi Qi, Tang Xing, He Xiuqiang, and Wen Ji-Rong
    In The Thirteenth International Conference on Learning Representations, ICLR , 2025
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  11. Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models
    Zhang Kexin, Lyu Fuyuan, Tang Xing, Liu# Dugang, Ma Chen, Ding Kaize, He Xiuqiang, and Liu Xue
    In Proceedings of the 18th ACM International Conference on Web Search and Data Mining, WSDM , 2025
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2024

  1. OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
    Weng* Yunpeng, Tang Xing, Xu Zhenhao, Lyu Fuyuan, Liu Dugang, Sun Zexu, and He Xiuqiang
    In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM , 2024
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  2. End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling
    Sun Zexu, Yang Hao, Liu# Dugang, Weng Yunpeng, Tang Xing, and He Xiuqiang
    In Proceedings of the 18th ACM Conference on Recommender Systems, RecSys, 2024
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  3. Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
    Tang Xing, Qiao* Yang, Lyu* Fuyuan, Liu Dugang, and He Xiuqiang
    In Proceedings of the 18th ACM Conference on Recommender Systems, RecSys, 2024
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  4. Masked Random Noise for Communication-Efficient Federated Learning
    Li Shiwei, Cheng Yingyi, Wang Haozhao, Tang Xing, Xu Shijie, Luo Weihong, Li Yuhua, Liu Dugang, He Xiuqiang, and Li Ruixuan
    In Proceedings of the 31st ACM International Conference on Multimedia, MM, 2024
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  5. Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing
    He Bowei, Weng Yunpeng, Tang Xing, Cui Ziqiang, Sun Zexu, Chen Liang, He Xiuqiang, and Ma Chen
    In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD , 2024
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  6. FedBAT: Communication-efficient Federated Learning via Learnable Binarization
    Li Shiwei, Xu Wenchao, Wang# Haozhao, Tang Xing, Qi Yining, Xu Shijie, Luo Weihong, Li Yuhua, He Xiuqiang, and Li# Ruixuan
    In 41st International Conference on Machine Learning, ICML, 2024
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  7. AutoDCS: Automated Decision Chain Selection in Deep Recommender Systems
    Liu Dugang, Xian Shenxian, Wu Yuhao, Yang Chaohua, Tang Xing, He Xiuqiang, and Ming Zhong
    In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2024
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  8. Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing
    Sun Zexun, Liu Dugang, Tang Xing, Weng Yunpeng, and He Xiuqiang
    In Database Systems for Advanced Applications - 29th International Conference, DASFAA, 2024
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  9. RecDCL: Dual Contrastive Learning for Recommendation
    Zhang Dan, Geng Yangliao, Gong Wenwen, Qi Zhongang, Chen Zhiyu, Tang Xing, Shan Ying, Dong Yuxiao, and Tang Jie
    In Proceedings of the ACM Web Conference 2024,WebConf, 2024
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  10. Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks
    Cui Ziqiang, Tang Xing, Qiao Yang, He Bowei, Chen Liang, He Xiuqiang, and Ma Chen
    In Proceedings of the 2024 SIAM International Conference on Data Mining,SDM, 2024
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  11. Embedding Compression in Recommender Systems:A Survey
    Li Shiwei, Guo Huifeng, Tang Xing, Tang Ruiming, Hou Lu, Li Ruixuan, and Zhang Rui
    ACM Computing Surveys, 2024
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  12. MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems
    Liu* Dugang, Yang* Chaohua, Tang Xing, Wang Yejing, Lyu Fuyuan, Luo Weihong, He Xiuqiang, Ming Zhong, and Zhao Xiangyu
    In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM, 2024
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2023

  1. Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
    Lyu Fuyuan, Tang Xing, Liu Dugang, Ma Chen, Luo Weihong, Chen Liang, He Xiuqiang, and Liu Xue
    In 37th Annual Conference on Neural Information Processing Systems, NeurIPS, 2023
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  2. Prior-guided Accuracy-bias Tradeoff Learning for CTR Prediction in Multimedia Recommendation
    Liu Dugang, Qiao Yang, Tang Xing, Chen Liang, He Xiuqiang, and Ming Zhong
    In Proceedings of The 30th ACM International Conference on Multimedia, MM, 2023
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  3. OptMSM: Optimizing Multi-Scenario Modeling for Click-Through Rate Prediction
    Tang Xing, Qiao* Yang, Fu* Yuwen, Lyu Fuyuan, Liu Dugang, and He Xiuqiang
    In European Conference on Machine Learning and Knowledge Discovery in Databases, ECML-PKDD, 2023
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  4. Expected Transaction Value Optimization for Precise Marketing in FinTech Platforms
    Weng Yunpeng, Tang Xing, Chen Liang, Liu Dugang, and He Xiuqiang
    In International Workshop on Deep Learning Practice for High-Dimensional Sparse Data, DLP@Recsys, 2023
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  5. AutoOpt: Automatic Hyperparameter Scheduling and Optimization for Deep Click-through Rate Prediction
    Li* Yujun, Tang Xing, Chen* Bo, Huang Yimin, Tang Ruiming, and Li Zhenguo
    In Proceedings of the 17th ACM Conference on Recommender Systems, RecSys, 2023
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  6. Explicit Feature Interaction-aware Uplift Network for Online Marketing
    Liu Dugang, Tang Xing, Han Gao, Lyu Fuyuan, and He# Xiuqiang
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD, 2023
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  7. Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing
    Weng* Yunpeng, Tang Xing, Chen Liang, and He Xiuqiang
    In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR, 2023
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  8. Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction
    Li Shiwei, Guo Huifeng, Hou Lu, Zhang Wei, Tang Xing, Tang Ruiming, Zhang Rui, and Li Ruixuan
    In Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI, 2023
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  9. DIWIFT: Discovering Instance-wise Influential Features for Tabular Data
    Liu* Dugang, Cheng* Pengxiang, Zhu* Hong, Tang Xing, Chen Yanyu, Wang Xiaoting, Pan Weike, Ming Zhong, and He Xiuqiang
    In Proceedings of the ACM Web Conference 2023, WebConf, 2023
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  10. Optimizing Feature Set for Click-Through Rate Prediction
    Lyu* Fuyuan, Tang Xing, Liu Dugang, Chen Liang, He Xiuqiang, and Liu Xue
    In Proceedings of the ACM Web Conference 2023, WebConf, 2023
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  11. Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation
    Liu Dugang, Yang Qiao, Tang Xing, Chen Liang, He Xiuqiang, Pan Weike, and Ming Zhong
    In Database Systems for Advanced Applications - 28th International Conference, DASFAA, 2023
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2022

  1. OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction
    Lyu* Fuyuan, Tang Xing, Zhu Hong, Guo Huifeng, Zhang Yingxue, Tang Ruiming, and Liu Xue
    In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, CIKM, 2022
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  2. Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction
    Lyu* Fuyuan, Tang Xing, Guo Huifeng, Tang Ruiming, He Xiuqiang, Zhang Rui, and Liu Xue
    In 38th IEEE International Conference on Data Engineering, ICDE, 2022
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2021

  1. Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network
    Ouyang* Yi, Guo Bin, Tang Xing, He Xiuqiang, Xiong Jian, and Yu Zhiwen
    ACM Transaction on Knowledge Discovery from Data, 2021
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2020

  1. AutoConjunction: Adaptive Model-based Feature Conjunction for CTR Prediction
    Chang* Chih-Yao, Tang Xing, Yuan Bo-Wen, Hsia Jui-Yang, Liu Zhirong, Dong Zhenhua, He Xiuqiang, and Lin Chih-Jen
    In 21st IEEE International Conference on Mobile Data Management, MDM, 2020
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2016

  1. A Data-Based Approach to Discovering Multi-Topic Influential Leaders
    Tang Xing, Miao Qiguang, Yu Shangshang, and Quan Yining
    PLOS ONE, Jul 2016
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2015

  1. Predicting individual retweet behavior by user similarity: A multi-task learning approach
    Tang Xing, Miao Qiguang, Quan Yi-Ning, Tang Jie, and Deng Kai
    Knowledge-Based System, Jul 2015
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2014

  1. A Novel Email Virus Propagation Model with Local Group
    Miao Qiguang, Tang Xing, and Quan Yi-Ning
    In IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing, UIC, Jul 2014
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