Publications (13)
Personalized Query Auto-Completion for Long and Short-Term Interests with Adaptive Detoxification Generation
Zhibo Wang, Xiaoze Jiang, Zhiheng Qin +2
Query auto-completion (QAC) plays a crucial role in modern search systems. However, in real-world applications, there are two pressing challenges that still need to be addressed. F…
Unified Generative Search and Recommendation
Teng Shi, Jun Xu, Xiao Zhang +4
Modern commercial platforms typically offer both search and recommendation functionalities to serve diverse user needs, making joint modeling of these tasks an appealing direction.…
CroPS: Improving Dense Retrieval with Cross-Perspective Positive Samples in Short-Video Search
Ao Xie, Jiahui Chen, Quanzhi Zhu +4
Dense retrieval has become a foundational paradigm in modern search systems, especially on short-video platforms. However, most industrial systems adopt a self-reinforcing training…
LLM4PR: Improving Post-Ranking in Search Engine with Large Language Models
Yang Yan, Yihao Wang, Chi Zhang +8
Alongside the rapid development of Large Language Models (LLMs), there has been a notable increase in efforts to integrate LLM techniques in information retrieval (IR) and search e…
Query-dominant User Interest Network for Large-Scale Search Ranking
Tong Guo, Xuanping Li, Haitao Yang +9
Historical behaviors have shown great effect and potential in various prediction tasks, including recommendation and information retrieval. The overall historical behaviors are var…
CounterCLR: Counterfactual Contrastive Learning with Non-random Missing Data in Recommendation
Jun Wang, Haoxuan Li, Chi Zhang +4
Recommender systems are designed to learn user preferences from observed feedback and comprise many fundamental tasks, such as rating prediction and post-click conversion rate (pCV…