Kairui Fu

AI4GC Lab

Kairui Fu

Industrial-scale RecommendationGenerative RetrievalLLM-based Recommendation
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About Me

Hi! I am Kairui Fu, a graduated Master student from AI4GC Lab at Zhejiang University. I received both my M.S. and B.S. degrees from the College of Computer Science and Technology at Zhejiang University, advised by Prof. Kun Kuang and Prof. Shengyu Zhang.

My research focuses on the generalizability and personalization of recommender systems. I am especially interested in LLM-based recommendation, generative retrieval, and efficient inference for large recommender systems over long user interaction sequences.

I was also fortunate to conduct research on generative retrieval for recommendation at Taobao & Tmall Group, Alibaba.

During AI4GC

During my time at AI4GC Lab, my research mainly followed three directions:

  1. Device-cloud recommendation. Customizing and adapting recommendation models across heterogeneous devices and cloud systems, covering DIET, Forward-OFA, CHORD, and real-time parameter editing for device data shifts.

  2. LLM-based recommendation. Extending large language models to recommendation and long-sequence user modeling, including ThinkRec and MALLOC.

  3. Industrial-scale recommendation systems. Building large-scale retrieval systems for Taobao recommendation scenarios, including PI2I, FORGE, and RankGR, with online deployment and measurable business gains.

Selected Papers

arXiv2026

Deployed on Taobao

RankGR: Rank-Enhanced Generative Retrieval with Listwise Direct Preference Optimization in Recommendation

Kairui Fu, Changfa Wu, Kun Yuan, Binbin Cao, Dunxian Huang, Yuliang Yan, Junjun Zheng, Jianning Zhang, Silu Zhou, Jian Wu, Kun Kuang

Paper

WWW2026

Deployed on Taobao

PI2I: A Personalized Item-Based Collaborative Filtering Retrieval Framework

Shaoqing Wang, Yingcai Ma, Kairui Fu, Ziyang Wang, Dunxian Huang, Yuliang Yan, Jian Wu

PaperHugging Face

arXiv2026

MALLOC: Benchmarking the Memory-aware Long Sequence Compression for Large Sequential Recommendation

Qihang Yu, Kairui Fu, Zhaocheng Du, Yuxuan Si, Kaiyuan Li, Weihao Zhao, Zhicheng Zhang, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Shengyu Zhang, Kun Kuang, Fei Wu

PaperProject

ACM MM2025

CHORD: Customizing Hybrid-precision On-device Model for Sequential Recommendation with Device-cloud Collaboration

Tianqi Liu, Kairui Fu, Shengyu Zhang✉, Wenyan Fan, Zhaocheng Du, Jieming Zhu, Fan Wu, Fei Wu

Paper

ACM MM2025

Tackling Device Data Distribution Real-time Shift via Prototype-based Parameter Editing

Zheqi Lv, Wenqiao Zhang, Kairui Fu, Qi Tian, Shengyu Zhang✉, Jiajie Su, Jingyuan Chen, Kun Kuang, Fei Wu

Paper

KDD2025

Forward Once for All: Structural Parameterized Adaptation for Efficient Cloud-coordinated On-device Recommendation

Kairui Fu, Zheqi Lv, Shengyu Zhang✉, Fan Wu, Kun Kuang

PaperProject

KDD2024

DIET: Customized Slimming for Incompatible Networks in Sequential Recommendation

Kairui Fu, Shengyu Zhang✉, Zheqi Lv, Jingyuan Chen, Jiwei Li

Paper

CICAI2023

Best Paper

End-to-End Optimization of Quantization-Based Structure Learning and Interventional Next-Item Recommendation

Kairui Fu, Qiaowei Miao, Shengyu Zhang✉, Kun Kuang, Fei Wu

Paper

Education

  • M.S. in Computer Science and Technology, Zhejiang University, 2023.09 - 2026.03
  • B.S. in Computer Science and Technology, Turing Class, Chu Kochen Honors College, Zhejiang University, 2019.09 - 2023.06

Internships

  • Taobao & Tmall Group, Alibaba, 2025.05 - 2026.03
  • Huawei Noah's Ark Lab, 2025.02 - 2025.05