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Zhu Sun

Zhu Sun has 2 papers in our library, in 2026, most of them on Language models & pretraining; often with Jie Zhang, Tianjun Wei, Yingpeng Du.

2 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 24 · 132 works · 2,172 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 2 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #13248

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Singapore University of Technology and DesignSingapore · Singapore2024–2026 · 46 papersEmployment since 2024 · Assistant Professor, Information Systems Technology and Designcurrent🎓Nanyang Technological UniversitySingapore · Singapore2015–2026 · 22 paperscurrent🎓China University of Petroleum, BeijingBeijing · China2026 · 1 papercurrent🏛️Agency for Science, Technology and ResearchSingapore · Singapore2019–2025 · 27 papers🔬Institute of High Performance ComputingSingapore · Singapore2022–2025 · 22 papers🎓Shanghai UniversityShanghai · China2007–2014 · 15 papers🎓Macquarie UniversitySydney · Australia2013–2024 · 11 papersEmployment

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksDecision Sciences · 2 worksInformation Systems · 2 worksManagement Science and Operations Research · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in Recommendation (2026 · 1 citation)
    Recommender systems need realistic user simulators for offline evaluation, because online A/B tests are slow and raise privacy issues.
  2. Adaptive and Representative Multi-Interest Modeling for Recommendation with Large Language Model (2026)
    Multi-interest recommenders give each user several representation vectors. Most of them group items with heuristics such as embedding similarity or co-occurrence, and these heuristics break down when interactions are sparse or side information is incomplete. The authors propose LARMI, a framework in which an LLM…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. An Attentional Recurrent Neural Network for Personalized Next Location Recommendation ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetQing Guo et al.2020 · 125 citations
  2. Mirroring Users: Towards Building Preference-aligned User Simulator with User Feedback in RecommendationAnnual Meeting of the Association for Computational Linguistics (ACL)Tianjun Wei, Huizhong Guo, Yingpeng Du, et al.2026 · 1 citation
  3. Adaptive and Representative Multi-Interest Modeling for Recommendation with Large Language ModelFindings of the Association for Computational LinguisticsZiyan Wang, Yingpeng Du, Tianjun Wei, et al.2026

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 2 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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