Yu Zhang

According to our database, Yu Zhang authored at least 23 papers between 2022 and 2026.

Collaborative distances:

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

2026

Selective Test-Time Compute Scaling for Click-Through Rate Prediction via Uncertainty-Triggered Feature Path Exploration.

Moyu Zhang, Yun Chen, Yujun Jin, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

CoRR, May, 2026

Self-Balancing Gradient Allocation for Heterogeneity-Aware Feature Generation in Click-Through Rate Prediction.

Moyu Zhang, Yun Chen, Yujun Jin, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

CoRR, May, 2026

LWGR: Lagrangian-Constrained Personalized World Knowledge for Generative Recommendation.

Lingyu Mu, Hao Deng, Haibo Xing, Kaican Lin, Zhitong Zhu, Yu Zhang, Xiaoyi Zeng, Zhengxiao Liu, Zheng Lin, Jinxin Hu

CoRR, May, 2026

RCLRec: Reverse Curriculum Learning for Modeling Sparse Conversions in Generative Recommendation.

Yulei Huang, Hao Deng, Haibo Xing, Jinxin Hu, Chuanfei Xu, Zulong Chen, Yu Zhang, Xiaoyi Zeng

CoRR, March, 2026

AgenticRS-EnsNAS: Ensemble-Decoupled Self-Evolving Architecture Search.

Yun Chen, Moyu Zhang, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

CoRR, March, 2026

Deferred is Better: A Framework for Multi-Granularity Deferred Interaction of Heterogeneous Features.

Yi Xu, Moyu Zhang, Chaofan Fan, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

CoRR, March, 2026

Bridging Sequential and Contextual Features with a Dual-View of Fine-grained Core-Behaviors and Global Interest-Distribution.

Yi Xu, Chaofan Fan, Moyu Zhang, Jinxin Hu, Jiahao Wang, Hao Zhang, Shizhun Wang, Yu Zhang, Xiaoyi Zeng

CoRR, March, 2026

Learning to Reflect and Correct: Towards Better Decoding Trajectories for Large-Scale Generative Recommendation.

Haibo Xing, Hao Deng, Lingyu Mu, Jinxin Hu, Yu Zhang, Xiaoyi Zeng, Jing Zhang

CoRR, February, 2026

Masked Diffusion Generative Recommendation.

Lingyu Mu, Hao Deng, Haibo Xing, Jinxin Hu, Yu Zhang, Xiaoyi Zeng, Jing Zhang

CoRR, January, 2026

Bionic soft robotic glove with EMG-based gesture and grip strength synchronized prediction for grasping assistance.

Jing Zhang, Aibin Zhu, Bingsheng Bao, Meng Li, Yu Zhang, Jing Wang, Xinyu Wu, Chunli Zheng, Xiao Li

Biomed. Signal Process. Control., 2026

Infer As You Train: A Symmetric Paradigm of Masked Generative for Click-Through Rate Prediction.

Moyu Zhang, Yujun Jin, Yun Chen, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

Proceedings of the ACM Web Conference 2026, 2026

MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation.

Yi Xu, Moyu Zhang, Chenxuan Li, Zhihao Liao, Haibo Xing, Hao Deng, Jinxin Hu, Yu Zhang, Xiaoyi Zeng, Jing Zhang

Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, 2026

2025

MMQ-v2: Align, Denoise, and Amplify: Adaptive Behavior Mining for Semantic IDs Learning in Recommendation.

Yi Xu, Moyu Zhang, Chaofan Fan, Jinxin Hu, Xiaochen Li, Yu Zhang, Xiaoyi Zeng, Jing Zhang

CoRR, October, 2025

MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths.

Moyu Zhang, Yun Chen, Yujun Jin, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

CoRR, October, 2025

DGenCTR: Towards a Universal Generative Paradigm for Click-Through Rate Prediction via Discrete Diffusion.

Moyu Zhang, Yun Chen, Yujun Jin, Jinxin Hu, Yu Zhang

CoRR, August, 2025

ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems.

Haibo Xing, Kanefumi Matsuyama, Hao Deng, Jinxin Hu, Yu Zhang, Xiaoyi Zeng

Proceedings of the ACM on Web Conference 2025, 2025

LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction.

Xin Song, Xiaochen Li, Jinxin Hu, Hong Wen, Zulong Chen, Yu Zhang, Xiaoyi Zeng, Jing Zhang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

CSMF: Cascaded Selective Mask Fine-Tuning for Multi-Objective Embedding-Based Retrieval.

Hao Deng, Haibo Xing, Kanefumi Matsuyama, Moyu Zhang, Jinxin Hu, Hong Wen, Yu Zhang, Xiaoyi Zeng, Jing Zhang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation.

Hao Deng, Haibo Xing, Kanefumi Matsuyama, Yulei Huang, Jinxin Hu, Hong Wen, Jia Xu, Zulong Chen, Yu Zhang, Xiaoyi Zeng, Jing Zhang

Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025

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

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

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

Global-Distribution Aware Scenario-Specific Variational Representation Learning Framework.

Moyu Zhang, Yujun Jin, Jinxin Hu, Yu Zhang

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