Yongxiang Tang

According to our database, Yongxiang Tang authored at least 10 papers between 2022 and 2025.

Collaborative distances:

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

2025

Distribution-Guided Auto-Encoder for User Multimodal Interest Cross Fusion.

Moyu Zhang, Yongxiang Tang, Yujun Jin, Jinxin Hu, Yu Zhang

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

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

2024

Scenario-Adaptive Fine-Grained Personalization Network: Tailoring User Behavior Representation to the Scenario Context.

Moyu Zhang, Yongxiang Tang, Jinxin Hu, Yu Zhang

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

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