Yupeng Hou 侯宇蓬


yphou AT ucsd.edu

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I am a PhD student at UC San Diego, fortunate to be advised by Prof. Julian McAuley. During the summer of 2024, I worked as a student researcher at Google DeepMind. I obtained my M.E. and B.E. from Renmin University of China, advised by Prof. Wayne Xin Zhao, who leads the AI Box Lab. My recent research interests focus on generative recommendation, tokenization, and large language models.

📌 Pinned
  • Generative recommendation tutorials at [WWW 2025];
  • Check our newly released Amazon Reviews 2023 dataset! [🌐 Webpage] [🤗 HF datasets]
    The new dataset features up-to-date reviews (up to Sep. 2023) and larger sizes (570M reviews, 48M items, and 60B tokens).

Open Source Project

GitHub Repo stars GitHub forks
PyPI - Downloads - total PyPI - Downloads

Selected Publication [Full]

† denotes equal contribution
2025

  • ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation.

    Yupeng Hou, Jianmo Ni, Zhankui He, Noveen Sachdeva, Wang-Cheng Kang, Ed H. Chi, Julian McAuley, Derek Zhiyuan Cheng.

    ICML 2025 [paper] [bib] Spotlight 


    @inproceedings{hou2025actionpiece,
  title={{ActionPiece}: Contextually Tokenizing Action Sequences for Generative Recommendation},
  author={Yupeng Hou and Jianmo Ni and Zhankui He and Noveen Sachdeva and Wang-Cheng Kang and Ed H. Chi and Julian McAuley and Derek Zhiyuan Cheng},
  booktitle={{ICML}},
  year={2025}
}

  • Generating Long Semantic IDs in Parallel for Recommendation.

    Yupeng Hou, Jiacheng Li, Ashley Shin, Jinsung Jeon, Abhishek Santhanam, Wei Shao, Kaveh Hassani, Ning Yao, Julian McAuley.

    KDD 2025 [bib] 


    @inproceedings{hou2025rpg,
  title={Generating Long Semantic IDs in Parallel for Recommendation},
  author={Yupeng Hou and Jiacheng Li and Ashley Shin and Jinsung Jeon and Abhishek Santhanam and Wei Shao and Kaveh Hassani and Ning Yao and Julian McAuley},
  booktitle={{KDD}},
  year={2025}
}

2024

  • Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation.

    Bowen Zheng, Yupeng Hou, Hongyu Lu, Yu Chen, Wayne Xin Zhao, Ji-Rong Wen.

    ICDE 2024 [paper] [code] [bib] 


    @inproceedings{zheng2024lcrec,
  title={Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation},
  author={Bowen Zheng and Yupeng Hou and Hongyu Lu and Yu Chen and Wayne Xin Zhao and Ji-Rong Wen},
  booktitle={{ICDE}},
  year={2024}
}

  • Multi-Behavior Generative Recommendation.

    Zihan Liu†, Yupeng Hou†, Julian McAuley.

    CIKM 2024 [paper] [code] [bib] 


    @inproceedings{liu2024mbgen,
  title={Multi-Behavior Generative Recommendation},
  author={Zihan Liu and Yupeng Hou and Julian McAuley},
  booktitle={{CIKM}},
  year={2024}
}

  • Large Language Models are Zero-Shot Rankers for Recommender Systems.

    Yupeng Hou†, Junjie Zhang†, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, Wayne Xin Zhao.

    ECIR 2024 [paper] [code] [bib] 


    @inproceedings{hou2024llmrank,
  title={Large Language Models are Zero-Shot Rankers for Recommender Systems},
  author={Yupeng Hou and Junjie Zhang and Zihan Lin and Hongyu Lu and Ruobing Xie and Julian McAuley and Wayne Xin Zhao},
  booktitle={{ECIR}},
  year={2024}
}

2023

  • Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders.

    Yupeng Hou, Zhankui He, Julian McAuley, Wayne Xin Zhao.

    WWW 2023 [paper] [code] [bib] 


    @inproceedings{hou2023vqrec,
  author = {Yupeng Hou and Zhankui He and Julian McAuley and Wayne Xin Zhao},
  title = {Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders},
  booktitle={{WWW}},
  year = {2023}
}

2022

  • Towards Universal Sequence Representation Learning for Recommender Systems.

    Yupeng Hou†, Shanlei Mu†, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen.

    KDD 2022 [paper] [code] [poster] [slides] [bib] 


    @inproceedings{hou2022unisrec,
  author = {Yupeng Hou and Shanlei Mu and Wayne Xin Zhao and Yaliang Li and Bolin Ding and Ji-Rong Wen},
  title = {Towards Universal Sequence Representation Learning for Recommender Systems},
  booktitle = {{KDD}},
  year = {2022}
}

  • RecBole 2.0: Towards a More Up-to-Date Recommendation Library.

    Wayne Xin Zhao, Yupeng Hou†, Xingyu Pan†, Chen Yang, Zeyu Zhang, Zihan Lin, Jingsen Zhang, Shuqing Bian, Jiakai Tang, Wenqi Sun, Yushuo Chen, Lanling Xu, Gaowei Zhang, Zhen Tian, Changxin Tian, Shanlei Mu, Xinyan Fan, Xu Chen, Ji-Rong Wen.

    CIKM 2022 Resource Track. [paper] [GitHub] [poster] [slides] [bib] Best Resource Paper Runner-up. 


    @inproceedings{zhao2022recbole2,
  title={RecBole 2.0: Towards a More Up-to-Date Recommendation Library},
  author={Wayne Xin Zhao and Yupeng Hou and Xingyu Pan and Chen Yang and Zeyu Zhang and Zihan Lin and Jingsen Zhang and Shuqing Bian and Jiakai Tang and Wenqi Sun and Yushuo Chen and Lanling Xu and Gaowei Zhang and Zhen Tian and Changxin Tian and Shanlei Mu and Xinyan Fan and Xu Chen and Ji-Rong Wen},
  booktitle={{CIKM}},
  year={2022}
}

  • Modeling Two-Way Selection Preference for Person-Job Fit.

    Chen Yang, Yupeng Hou, Yang Song, Tao Zhang, Ji-Rong Wen, Wayne Xin Zhao.

    RecSys 2022 [paper] [code] [bib] Best Student Paper Runner-up. 


    @inproceedings{yang2022dpgnn,
  author = {Chen Yang and Yupeng Hou and Yang Song and Tao Zhang and Ji-Rong Wen and Wayne Xin Zhao},
  title = {Modeling Two-Way Selection Preference for Person-Job Fit},
  booktitle = {{RecSys}},
  year = {2022}
}

2021

  • RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms.

    Wayne Xin Zhao, Shanlei Mu†, Yupeng Hou†, Zihan Lin, Kaiyuan Li, Yushuo Chen, Yujie Lu, Hui Wang, Changxin Tian, Xingyu Pan, Yingqian Min, Zhichao Feng, Xinyan Fan, Xu Chen, Pengfei Wang, Wendi Ji, Yaliang Li, Xiaoling Wang, Ji-Rong Wen.

    CIKM 2021 Resource Track. [paper] [website] [GitHub] [datasets] [bib] 


    @inproceedings{zhao2021recbole,
  author = {Zhao, Wayne Xin and Mu, Shanlei and Hou, Yupeng and Lin, Zihan and Chen, Yushuo and Pan, Xingyu and Li, Kaiyuan and Lu, Yujie and Wang, Hui and Tian, Changxin and Min, Yingqian and Feng, Zhichao and Fan, Xinyan and Chen, Xu and Wang, Pengfei and Ji, Wendi and Li, Yaliang and Wang, Xiaoling and Wen, Ji-Rong},
  title = {RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms},
  year = {2021},
  booktitle = {{CIKM}},
}

Education

Experience

Service

  • Web Chair @ DSAA 2024
  • Co-organizing Personalized Generative AI @ CIKM 2023.
  • Program Committee / Conference Reviewer: ICML (2024-2025), ICLR (2024-2025), NeurIPS (2023-2025), KDD (2022-2025), WWW (2024-2025), SIGIR (2023-2025), RecSys (2023-2025), ACL Rolling Review (Oct 2024), AISTATS (2025), AAAI (2023-2025), CIKM (2024), SDM (2024), LoG (2022-2024), SIGIR-AP (2023-2024), EMNLP (2023), ECML-PKDD (2022-2023), WSDM (2022), and Workshops & Symposiums.
    • GenAIRecP @ KDD 2025 & KDD 2024, GENNEXT @ SIGIR 2025, LLM4Good @ UMAP 2025, SoCal NLP 2024, PGAI @ CIKM 2023
  • Journal Reviewer: TKDE, TOIS, TORS, TKDD, IPM, TALLIP.

Teaching

Award

  • Wu Yuzhang Scholarship (the highest honor for RUC students, 10 per year), Renmin Univ. of China, 2023.
  • National Scholarship, Ministry of Education of China, 2022.
  • Star of the Graduates (10 per year), Renmin Univ. of China, 2020.
  • Silver Medal, The ICPC Asia-East Continent Final, Xi'an Site, 2018.

Talk

  • Towards Large Generative Recommendation Models: A Tokenization Perspective.
    • 2025.05, UQ Data Science Seminar, The University of Queensland. (To appear)
    • 2025.05, Lab for Data Science, University of Science and Technology of China (To appear)
  • Improving General and Session-based Recommendation via Contrastive Learning.

Misc

  • Blogs and patents (in CN)
  • I was passionate about algorithmic competition (e.g., ACM-ICPC) and have contributed algorithm problems to NOIP, CSP-J/S for several years. Click [here] to check out all the problems I have contributed.
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