Xialong Liu

According to our database, Xialong Liu authored at least 18 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

R&F-Inventory: A Large-Scale Dataset for Monotonic Inventory Estimation in Reach and Frequency Advertising.

Yunshan Peng, Ji Wu, Wentao Bai, Yunke Bai, Jinan Pang, Wenzheng Shu, Yanxiang Zeng, Xialong Liu, Peng Jiang

CoRR, April, 2026

Fairness-Aware Design for Contextual Experiments: Guaranteeing Reliability and Equity in Heterogeneous Subgroups.

Guangyan Gan, Ling Zhang, Yanhua Cheng, Yongxiang Tang, Kaiyuan Li, Xialong Liu, Peng Jiang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

VQL: An End-to-End Context-Aware Vector Quantization Attention for Ultra-Long User Behavior Modeling.

Kaiyuan Li, Yongxiang Tang, Yanhua Cheng, Yong Bai, Yanxiang Zeng, Chao Wang, Xialong Liu, Peng Jiang

CoRR, August, 2025

INFNet: A Task-aware Information Flow Network for Large-Scale Recommendation Systems.

Kaiyuan Li, Dongdong Mao, Yongxiang Tang, Yanhua Cheng, Yanxiang Zeng, Chao Wang, Xialong Liu, Peng Jiang

CoRR, August, 2025

Learning Monotonic Probabilities with a Generative Cost Model.

Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu, Chenchen Jiao, Yanxiang Zeng, Ning Luo, Pengjia Yuan, Xialong Liu, Peng Jiang

CoRR, June, 2025

CHIME: A Compressive Framework for Holistic Interest Modeling.

Yong Bai, Rui Xiang, Kaiyuan Li, Yongxiang Tang, Yanhua Cheng, Xialong Liu, Peng Jiang, Kun Gai

CoRR, April, 2025

BBQRec: Behavior-Bind Quantization for Multi-Modal Sequential Recommendation.

Kaiyuan Li, Rui Xiang, Yong Bai, Yongxiang Tang, Yanhua Cheng, Xialong Liu, Peng Jiang, Kun Gai

CoRR, April, 2025

Reward Balancing Revisited: Enhancing Offline Reinforcement Learning for Recommender Systems.

Wenzheng Shu, Yanxiang Zeng, Yongxiang Tang, Teng Sha, Ning Luo, Yanhua Cheng, Xialong Liu, Fan Zhou, Peng Jiang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

EBaReT: Expert-guided Bag Reward Transformer for Auto Bidding.

Kaiyuan Li, Pengyu Wang, Yunshan Peng, Pengjia Yuan, Yanxiang Zeng, Rui Xiang, Yanhua Cheng, Xialong Liu, Peng Jiang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Optimal Return-to-Go Guided Decision Transformer for Auto-Bidding in Advertisement.

Hao Jiang, Yongxiang Tang, Yanxiang Zeng, Pengjia Yuan, Yanhua Cheng, Teng Sha, Xialong Liu, Peng Jiang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain.

Rui Xia, Yanhua Cheng, Yongxiang Tang, Xiaocheng Liu, Xialong Liu, Lisong Wang, Peng Jiang

Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining, 2025

Learning Monotonic Probabilities with a Generative Cost Model.

Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu, Jiaochen Chen, Yanxiang Zeng, Ning Luo, Pengjia Yuan, Xialong Liu, Peng Jiang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Expert-Guided Diffusion Planner for Auto-Bidding.

Yunshan Peng, Wenzheng Shu, Jiahao Sun, Yanxiang Zeng, Jinan Pang, Wentao Bai, Yunke Bai, Xialong Liu, Peng Jiang

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2023

Tutorial: Data Denoising Metrics in Recommender Systems.

Pengfei Wang, Chenliang Li, Lixin Zou, Zhichao Feng, Kaiyuan Li, Xiaochen Li, Xialong Liu, Shangguang Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Soft Retargeting Network for Click Through Rate Prediction.

Xiaochen Li, Xin Song, Pengjia Yuan, Xialong Liu, Yu Zhang

CoRR, 2022

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction.

Xiaochen Li, Rui Zhong, Jian Liang, Xialong Liu, Yu Zhang

CoRR, 2022

Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction.

Xiaochen Li, Jian Liang, Xialong Liu, Yu Zhang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems.

Yongxiang Tang, Wentao Bai, Guilin Li, Xialong Liu, Yu Zhang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022