Weicong Qin (秦维聪)
“A ship in harbor is safe, but that is not what ships are built for.” -Grace Hopper
He is currently a second-year master’s student at Gaoling School of Artificial Intelligence, Renmin University of China. He is working in RUC-IIR-lab. His supervisors are AP. Xiao Zhang and Prof. Jun Xu. His major research interests are about Rec & Search with LLM, Generative Retrieval etc.
NEWS
🎤 ACL’25 Vienna • 28 Jul (Mon) ➤ Oral Pres. | RecSys’25 Prague • 22 Sep ➤ Oral Pres. | EMNLP’25 Suzhou • 5 Nov (Wed).
👋 Look forward to exchanging
🎉 Job seeking now | 2026 Graduate | Rec & Search with LLM, Generative Retrieval
🎯 Strong interest in Talent Programs of leading companies
📬 Welcome recruiters/industry peers to connect (qwc -AT- ruc.edu.cn)
Education
- 09.2023-present Master’s Candidate, Gaoling School of Artificial Intelligence, Renmin University of China.
- 09.2019-06.2023 B.E., School of Computer Science and Technology, Huazhong University of Science and Technology.
Publications
All are FIRST-AUTHOR publications (2A+3B for now), except the last one which is a CO-FIRST-AUTHOR publication
- [Search&Rec with LLM] “MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation Alignment.” ACL’25 Long Paper Main Conference (Oral)
- [Generative Retrieval] “Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach.” SIGIR’24 Full Paper (Oral).
- [LLM+RL for Rec] “Enhancing Sequential Recommendations through Multi-Perspective Reflections and Iteration.” RecSys’24 Full Paper Spotlight Oral.
- [Search with consultations] “Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search.” EMNLP’25 Long Paper Main Conference
- [Retrieval in Noisy data] “Uncertainty-aware evidential learning for legal case retrieval with noisy correspondence.” Information Sciences (2025): 121915.
- [Generative Retrieval with RQ-VAE] “Legal Document Generative Retrieval in Multi-Law-Code Scenarios” TOIS Under Review.
- [LLM for Legal Domain] “Exploring the Nexus of Large Language Models and Legal Systems: A Short Survey.” Arxiv’24.
- [Theoretical Derivation of LLM4Rec] “Decoding Recommendation Behaviors of In-Context Learning LLMs Through Gradient Descent.” Arxiv’24.
Internship
Lenovo AI Research Institute | Algorithm Research Intern Mar 2024 - Feb 2023
- Developed personalized search & recommendation algorithms using large-scale user data, resulting in several first/co-first author papers and multiple patent applications.
ByteDance (TikTok) | Algorithm Intern Feb 2023 - Jun 2023
- User-Generated Content (UGC) Distribution Optimization and Cold-Start Flow Construction: Optimized the content distribution recall and utilized user short-term and long-term interest profiles to better match users with content likely to generate meaningful discussion, significantly improving key engagement metrics post-launch.
- UGC Cold-Start Flow Construction: Designed and built a UGC cold-start flow to boost initial traffic for new user-generated content, preventing High-Potential Comment Section from being buried and fostering a healthier content ecosystem, significantly increasing submissions with informative comments.
Teaching
- Teaching Assistant, Retrieval and Recommendation in the Age of Artificial Intelligence, Spring 2024
Honor
- The First Award of Graduate Study Scholarship in Gaoling School of Artificial Intelligence, Renmin University of China
- Outstanding Graduate in Huazhong University of Science and Technology
- Honours Bachelor in Huazhong University of Science and Technology
- National Scholarship for Undergraduate Students
- National Encouragement scholarship in Huazhong University of Science and Technology
- Merit Student Scholarship in Huazhong University of Science and Technology