Yanhua’s current research focuses on large-scale machine learning for recommender systems. He has published papers in top-tier conference proceedings, including KDD, ICLR, and SIGIR, with a total of 1,000+ Google Scholar citations.

Previously, Yanhua led the base model team at Xiaohongshu, working on generative and multimodal recommendation. Before that, he spent two years at Baidu on Feed recommendation and four years at East China Normal University earning his Bachelor’s degree in the Department of Mathematics.

Selected Publications

A Metric for MLLM Alignment in Large-scale Recommendation
Yubin Zhang*, Yanhua Huang*, Haiming Xu, Mingliang Qi, Chang Wang, Jiarui Jin, Xiangyuan Ren, Xiaodan Wang, Ruiwen Xu
RecSys 2025 Workshop on Evaluating and Applying RecSys with LLMs
[Paper]

Towards Large-scale Generative Ranking
Yanhua Huang, Yuqi Chen, Xiong Cao, Rui Yang, Mingliang Qi, Yinghao Zhu, Qingchang Han, Yaowei Liu, Zhaoyu Liu, Xuefeng Yao, Yuting Jia, Leilei Ma, Yinqi Zhang, Taoyu Zhu, Liujie Zhang, Lei Chen, Weihang Chen, Min Zhu, Ruiwen Xu, Lei Zhang
KDD 2025 Workshop on GenAI for RecSys and Personalization
[Paper]

Learning Harmonized Representations for Speculative Sampling
Lefan Zhang, Xiaodan Wang, Yanhua Huang, Ruiwen Xu
ICLR 2025
[Paper] [Code] [Weight]

Sliding Spectrum Decomposition for Diversified Recommendation
Yanhua Huang, Weikun Wang, Lei Zhang, Ruiwen Xu
KDD 2021
[Paper]

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