Lei Li at HKBU

Post-doctoral Research Fellow

Department of Computer Science (CSD)
Hong Kong Baptist University (HKBU)

Biography

I am a post-doc supervised by Prof. Li Chen at the Department of Computer Science, Hong Kong Baptist University. I visited Rutgers University and did research with Dr. Yongfeng Zhang in 2023. Under their guidance and with the support from Hong Kong Research Grants Council (RGC) and Huawei, I have been investigating large language models for recommender systems. I did my Ph.D. at the same department, and my research focus was mainly on explainable recommendation with natural language generation.

Previously, I received my bachelor's degrees in computer science and mathematics from Shenzhen University, where I systematically studied recommender systems and information retrieval, under the supervision of Prof. Weike Pan.

Research Interests

Explainable Recommendation
Recommender Systems
Travel Planning
Large Language Models

Education

Ph.D. in Computer Science
Hong Kong Baptist University (HKBU), Aug. 2017 -- Jul. 2022
B.Eng. in Computer Science & B.Sc. in Mathematics
Shenzhen University (SZU), Sep. 2013 -- Jun. 2017

Selected Publications

Lei Li, Yongfeng Zhang, Dugang Liu, Li Chen. Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (COLING'24), pages 10146-10159, Turin, Italy, May 20--25, 2024.
[Paper] [Slides] [Poster] [arXiv] [Publisher] [概述]
Lei Li, Yongfeng Zhang, Li Chen. Prompt Distillation for Efficient LLM-based Recommendation. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM'23), pages 1348-1357, Birmingham, United Kingdom, October 21--25, 2023.
[Paper] [Slides] [Code] [Publisher]
Lei Li, Yongfeng Zhang, Li Chen. Personalized Prompt Learning for Explainable Recommendation. ACM Transactions on Information Systems (TOIS), volume 41 (4), article 103, pages 1-26, March 2023.
[arXiv] [Code] [Publisher] [概述]
Lei Li, Yongfeng Zhang, Li Chen. On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance. ACM Transactions on Intelligent Systems and Technology (TIST), volume 14 (2), article 21, pages 1-24, February 2023.
[arXiv] [Code] [Publisher] [概述]
Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo, Yongfeng Zhang. Improving Personalized Explanation Generation through Visualization. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL'22), pages 244-255, Dublin, Ireland, May 22--27, 2022.
[Publisher]
Lei Li. Natural Language Explanation for Recommendations and Beyond. Ph.D. Thesis, Hong Kong Baptist University, May 2022.
[Thesis] [Slides] [Ecosystem] [Archive] [小生态]
Lei Li, Yongfeng Zhang, Li Chen. Personalized Transformer for Explainable Recommendation. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL'21), pages 4947-4957, Bangkok, Thailand (Online), August 1--6, 2021. (oral paper)
[Paper] [Slides] [Code] [arXiv] [Publisher] [概述]
Lei Li, Yongfeng Zhang, Li Chen. EXTRA: Explanation Ranking Datasets for Explainable Recommendation. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), pages 2463-2469, Montreal, Canada (Online), July 11--15, 2021.
[Paper] [Poster] [Code] [Datasets] [arXiv] [Publisher] [概述]
Lei Li, Yongfeng Zhang, Li Chen. Generate Neural Template Explanations for Recommendation. Proceedings of the 29th ACM International Conference on Information & Knowledge Management (CIKM'20), pages 755-764, Galway, Ireland (Online), October 19--23, 2020.
[Paper] [Slides] [Code] [Toolkit] [Datasets] [Publisher] [概述]
Lei Li, Li Chen, Yongfeng Zhang. Towards Controllable Explanation Generation for Recommender Systems via Neural Template. Companion Proceedings of the Web Conference 2020 (WWW'20 Demo), pages 198-202, Taipei, Taiwan (Online), April 20--24, 2020.
[Paper] [Slides] [Video] [Publisher] [概述]

Online marks how many places I did not make it to, owing to COVID-19.

Talks

Lecture: "Conversational Recommender Systems and Recent Trends Driven by LLMs". RecSys'24 Summer School
Tutorial: "Large Language Models for Recommendation". RecSys'23
Talks:
- "Recent Trends in Recommender Systems Community (RecSys 2024)". Professors' Insights Gained from Top Conferences (Online). Nov. 4, 2024. Invited by Huawei
- "Large Language Models for Generative Recommendation". ConsumerBG AI Workshop Hong Kong, Huawei Hong Kong Research Center. Apr. 20, 2024
- "Large Language Models for Generative Recommendation". Computing Youth Forum, Hangzhou. Apr. 13, 2024. Invited by Huawei
- "Generating Recommendation Explanations with Transformer and Pre-trained Model". Data Science Lab, Korea Advanced Institute of Science & Technology (Online). Mar. 3, 2023. Invited by Dr. Husnu Baris Baydargil & Wenchao Dong
- "Improving Personalized Explanation Generation through Visualization". Department of Computer Science, University of Luxembourg (Online). Dec. 8, 2022. Invited by Dr. Bereket A. Yilma
- "How to Come up with Ideas and Do Research: Experience Sharing". COMP7160 Research Methods in Computer Science, CSD, HKBU. Oct. 19, 2021. Invited by Prof. Li Chen

Academic Services

Guest Editor: ACM Transactions on Recommender Systems (TORS) special issue on "Large Language Models for Recommender Systems", 2023
Workshop Organizer: "EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models". RecSys'24
Session Chair: CIKM'23 (Recommendation 9), WWW'23 (Multi-behavior Recommendation & Self-supervised Learning)
Program Committee Member: RecSys'24, WWW'23, RecSys'22
Invited Reviewer:
- IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, 2024
- ACM Transactions on Information Systems (TOIS), 2020, 2022, 2024
- ACM Transactions on Recommender Systems (TORS), 2023, 2024
- IEEE Transactions on Big Data (TBD), 2022
- International Journal of Human-Computer Studies (IJHCS), 2024
- ACM Transactions on Interactive Intelligent Systems (TiiS), 2021
- Neurocomputing (NEUCOM), 2018, 2024
- Knowledge-based Systems (KNOSYS), 2018
- Journal of Intelligent Information Systems (JIIS), 2021
External Reviewer: CIKM'24, SIGIR'21, WWW'21, WWW'19
Student Volunteer: EMNLP'19

Experiences

Aug. 2022 -- Present. Post-doctoral Research Fellow. CSD, HKBU, Hong Kong, China
Advisor: Prof. Li Chen, Mentor: Dr. Yongfeng Zhang
Feb. 2023 -- Jun. 2023. Visiting Researcher. CSD, Rutgers University, New Brunswick, USA
Advisor: Dr. Yongfeng Zhang
Aug. 2017 -- Jul. 2022. Ph.D. Student. CSD, HKBU, Hong Kong, China
Advisor: Prof. Li Chen, Mentors: Dr. Yongfeng Zhang & Dr. Ruihai Dong
Jun. 2019 -- Aug. 2019. Intern. Inspir.ai, Beijing, China
Mentor: Dr. Peng Peng
Jul. 2016 -- Aug. 2017. Undergraduate Research Assistant. Big Data Institute, SZU, Shenzhen, China
Advisor: Prof. Weike Pan
Mar. 2017 -- Jun. 2017. Research Exchange Student. CSD, HKBU, Hong Kong, China
Advisor: Prof. Li Chen
Aug. 2016 -- Nov. 2016. Intern. Suishou Technology, Shenzhen, China
Advisor: Prof. Weike Pan

Awards & Honors

Jun. 2024 -- Jun. 2025. Huawei Gift Fund. Huawei
Aug. 2022 -- Present. RGC Postdoctoral Fellowship Scheme (PDFS). Research Grants Council (RGC), Hong Kong
Sep. 2021. RPg Performance Award. CSD, HKBU
Aug. 2017 -- Aug. 2021. Research Postgraduate Studentship. HKBU
Jul. 2021. Student Travel Grant (Virtual). SIGIR'21
Jun. 2021. Research Excellence Award. Postgraduate Research Symposium (PG Day), CSD, HKBU
Oct. 2020. Student Travel Grant (Virtual). CIKM'20
Jun. 2020. Best Presentation Award. Postgraduate Research Symposium (PG Day), CSD, HKBU
Jun. 2018, 2019, 2020. Excellent Teaching Assistant Performance Award. HKBU
Feb. 2020. Teaching Assistant Performance Award. HKBU
Jun. 2017. Outstanding Graduate. SZU

Miscellaneous

Recently, I have been doing a podcast called After Ph.D. (《博士之后》), which is available on Spotify, Apple Podcast, 小宇宙 and 喜马拉雅.
I am a drone pilot. I created a mashup of all my aerial video clips recorded in 2021. Check it out to appreciate a different side of Hong Kong!
I love going outdoors and doing exercises, such as hiking, swimming and workout.
I am fond of reading. I have been reading Dune after seeing the movie.
I enjoy watching slow-paced Japanese movies, e.g., Little Forest, because they always bring me a sense of ease. Here are my favorites.
A fun fact about my name Lei is that it means garland in Hawaii. I hope I can travel there some day.

Department of Computer Science (CSD) Hong Kong Baptist University (HKBU)

Research Interests

Education

Department of Computer Science (CSD)
Hong Kong Baptist University (HKBU)