I am now working as a Lecturer in the Department of Computer Technology and Application at Qinghai University, and am also appointed as an Associate Researcher at Quancheng Laboratory. I obtained my Ph.D. (Computer Science) from the Australian National University supervised by Lexing Xie and Christian Walder, M.S. (Computer Science and Technology) from Tsinghua University supervised by Yiqun Liu, and B.E. (Computer Science and Technology) from Qinghai University. My major research interests are in Recommender Systems and Spam Detection, that is, recommending high-quality data that meets users’ personalized needs and detecting low-quality data.

Recent News

[2025-02] I will serve as Area Chair for ACM MM 2025.

[2025-02] Our paper “Diversity-Promoting Recommendation with Dual-Objective Optimization and Dual Consideration” is accepted by IEEE Transactions on Knowledge and Data Engineering.

[2024-11] A solo paper “Signed Latent Factors for Spamming Activity Detection” is accepted by IEEE Transactions on Information Forensics & Security.

[2024-10] A solo paper “A Generative and Discriminative Model for Diversity-Promoting Recommendation” is accepted by Information Systems.

[2024-06] Our paper “Pay Attention to Attention for Sequential Recommendation” is accepted by RecSys 2024.

[2024-06] Our paper “A Universal Sets- level Optimization Framework for Next Set Recommendation” is accepted by CIKM 2024.

[2024-05] Our paper “Probabilistic Attention for Sequential Recommendation” is accepted by KDD 2024.

[2024-01] I will serve as Area Chair for ACM MM 2024.

[2023-12] Our paper “Learning k-Determinantal Point Processes for Personalized Ranking” is accepted by ICDE 2024.

Selected Publications

1. Yuli Liu, YuAn Zhang. Diversity-Promoting Recommendation with Dual-Objective Optimization and Dual Consideration. Accepted by Transactions on Knowledge and Data Engineering (TKDE CCF A).
2. Yuli Liu. Signed Latent Factors for Spamming Activity Detection. Accepted by Transactions on Information Forensics & Security (TIFS CCF A) [ Paper].
3. Yuli Liu. A Generative and Discriminative Model for Diversity-Promoting Recommendation. Accepted by Information Systems (CCF B) [Paper].
4. Yuli Liu, Christian Walder, Lexing Xie, Yiqun Liu. Probabilistic Attention for Sequential Recommendation. KDD 2024 (CCF A) [ Paper , Code ]
5. Yuli Liu. Pay Attention to Attention: Attention Weight Refinement for Sequential Recommendation. RecSys 2024 (CCF B) [ Paper]
6. Yuli Liu, Christian Walder, and Lexing Xie. Structured Determinantal Point Process for Temporal Sets Prediction. CIKM2024 (CCF B) [ Paper]
7. Yuli Liu, Christian Walder, and Lexing Xie. Learning k-Determinantal Point Process for Recommendation. ICDE 2024 (CCF A) [ Paper , Code ]
8. Yuli Liu, Christian Walder, and Lexing Xie. Determinantal Point Process Likelihoods for Sequential Recommendation. SIGIR 2022 (CCF A). [ Paper , Code ]
9. Yuli Liu. Recommending Inferior Results: A General and Feature-Free Model for Spam Detection. Proceedings of the 29th ACM International Conference on Information & Knowledge Management. CIKM 2020 (CCF B). Paper
10. Yuli Liu, Yiqun Liu, Ke Zhou, Min Zhang, and Shaoping Ma. Detecting Collusive Spamming Activities in Community Question Answering. The 26th International World Wide Web Conference. WWW 2017 (CCF A). Paper
11. Yuli Liu, Yiqun Liu, Min Zhang, and Shaoping Ma. Pay me and i’ll follow you: Detection of crowdturfing following activities in microblog environment. IJCAI 2016 (CCF A). Paper
12. Yuli Liu, Yiqun Liu, Ke Zhou, Min Zhang, and Shaoping Ma. Detecting Promotion Campaigns in Query Auto Completion. The 25th ACM International on Conference on Information and Knowledge Management. CIKM 2016 (CCF B). Paper
13. Ning Su, Yiqun Liu, Zhao Li, Yuli Liu, Min Zhang, and Shaoping Ma. Detecting Crowdturfing “Add to Favorites” Activities in Online Shopping. The 27th International World Wide Web Conference. WWW 2018 (CCF A). Paper

Recent Professional Activities

PC Member: KDD 2024, TheWebConf 2024, and ACML 2024

Area Chair: ACM MM 2024

Honor and Awards

1. Excellent Master Graduate in Tsinghua University, 2017

   Top 100 out of 2500+ master degree graduates in Tsinghua University.

2. Excellent Master Graduate in Beijing, 2017

   Top 2 out of 70+ master degree graduates in Department of Computer Science and Technology Tsinghua University.

3. Graduate National Scholarship, 2016

   Top 10 out of 140+ graduate students in Department of Computer Science and Technology Tsinghua University.

4. Data61 Top-up PhD Scholarship, 2019

   Top-quality doctoral students in Australia’s data-skilled workforce.