I am a PhD student at UC San Diego, fortunate to be advised by Prof. Julian McAuley. I'm currently also working 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.
- 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).
Selected Publication [Full]
† denotes equal contributionPreprint
-
Inductive Generative Recommendation via Retrieval-based Speculation.
Yijie Ding†, Yupeng Hou†, Jiacheng Li, Julian McAuley.
preprint, arxiv:2410.02939. [paper] [code] [bib]
@article{ding2024specgr, title={Inductive Generative Recommendation via Retrieval-based Speculation}, author={Ding, Yijie and Hou, Yupeng and Li, Jiacheng and McAuley, Julian}, journal={arXiv preprint arXiv:2410.02939}, year={2024} }
-
Bridging Language and Items for Retrieval and Recommendation.
Yupeng Hou†, Jiacheng Li†, Zhankui He, An Yan, Xiusi Chen, Julian McAuley.
preprint, arxiv:2403.03952. [paper] [dataset page] [huggingface hub] [code] [bib]
@article{hou2024bridging, title={Bridging Language and Items for Retrieval and Recommendation}, author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian}, journal={arXiv preprint arXiv:2403.03952}, year={2024} }
-
A Survey of Large Language Models.
Wayne Xin Zhao, Kun Zhou†, Junyi Li†, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, Ji-Rong Wen.
preprint, arxiv:2303.18223. [paper] [GitHub] [bib]
@article{zhao2023llm_survey, title={A Survey of Large Language Models}, author={Wayne Xin Zhao and Kun Zhou and Junyi Li and Tianyi Tang and Xiaolei Wang and Yupeng Hou and Yingqian Min and Beichen Zhang and Junjie Zhang and Zican Dong and Yifan Du and Chen Yang and Yushuo Chen and Zhipeng Chen and Jinhao Jiang and Ruiyang Ren and Yifan Li and Xinyu Tang and Zikang Liu and Peiyu Liu and Jian-Yun Nie and Ji-Rong Wen}, journal={arXiv preprint arXiv:2303.18223}, year={2023} }
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} }
-
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} }
-
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.
@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} }
-
CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space.
Yupeng Hou, Binbin Hu, Zhiqiang Zhang, Wayne Xin Zhao.
SIGIR 2022 Short Paper. [paper] [code] [poster] [slides] [bib]
@inproceedings{hou2022core, author = {Yupeng Hou and Binbin Hu and Zhiqiang Zhang and Wayne Xin Zhao}, title = {CORE: Simple and Effective Session-based Recommendation within Consistent Representation Space}, booktitle = {{SIGIR}}, year = {2022} }
-
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning.
Zihan Lin†, Changxin Tian†, Yupeng Hou†, Wayne Xin Zhao.
@inproceedings{lin2022ncl, author={Zihan Lin and Changxin Tian and Yupeng Hou and Wayne Xin Zhao}, title={Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning}, booktitle={{WWW}}, 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
-
Ph.D., University of California, San Diego
2023 - present, Computer Science & Engineering
Advisor: Prof. Julian McAuley -
M.E., Renmin University of China
2020 - 2023, Gaoling School of Artificial Intelligence
Valedictorian
Advisor: Prof. Wayne Xin Zhao -
B.E., Renmin University of China
2016 - 2020, School of Information
Experience
-
Student Researcher, Google DeepMind
06/2024 - present,
with Dr. Jianmo Ni and Dr. Derek Zhiyuan Cheng.
-
Research Intern, Tencent
03/2023 - 06/2023, Weixin Group (WXG),
with Dr. Hongyu Lu.
-
Visiting Graduate Student, UC San Diego
06/2022 - 11/2022,
with Dr. Zhankui He and Prof. Julian McAuley.
-
Research Intern, DAMO Academy, Alibaba
11/2021 - 06/2022, Data Analytics and Intelligence Lab,
with Dr. Yaliang Li.
-
Research Intern, Ant Group
03/2021 - 09/2021, GraphML,
with Binbin Hu.
-
Research Intern, Boss Zhipin
09/2019 - 03/2021, NLP Center,
with Zekai Wang and Dr. Yang Song.
Service
- Web Chair @ DSAA 2024
- Co-organizing Personalized Generative AI @ CIKM 2023.
- Program Committee / Conference Reviewer: ICML (2024), ICLR (2024-2025), NeurIPS (2023-2024), KDD (2022-2025), WWW (2024-2025), SIGIR (2023-2024), ACL Rolling Review (Oct 2024), RecSys (2023-2024), 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.
- Journal Reviewer: TKDE, TOIS, TORS, TKDD, IPM, TALLIP.
Teaching
-
Teaching Assistant, University of California, San Diego
- 2024 Fall, CSE 258: Web Mining and Recommender Systems, with Julian McAuley.
-
Teaching Assistant, Renmin University of China
- 2020, 2021 Summer, Programming Training, with Wayne Xin Zhao.
[Project Page 2020] [Search Demo for 2021] [IR Evaluator for 2021] - 2018-2019 Fall, Introduction to Computer System, with Yunpeng Chai.
- 2018 Summer, Programming Training, with Feng Zhang.
- 2017-2018 Fall, Advanced Programming, with Wayne Xin Zhao.
- 2020, 2021 Summer, Programming Training, with Wayne Xin Zhao.
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
- Improving Recommendation via Contrastive Learning, 2022.04, BDAI Seminar, Renmin Univ. of China. [slides]
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.