3 papers
cs.IR2026
High Fidelity Textual User Representation over Heterogeneous Sources via Reinforcement Learning
Rajat Arora, Ye Tao, Jianqiang Shen +7
Effective personalization on large-scale job platforms requires modeling members based on heterogeneous textual sources, including profiles, professional data, and search activity…
cs.IR2025
Powering Job Search at Scale: LLM-Enhanced Query Understanding in Job Matching Systems
Ping Liu, Jianqiang Shen, Qianqi Shen +9
Query understanding is essential in modern relevance systems, where user queries are often short, ambiguous, and highly context-dependent. Traditional approaches often rely on mult…
cs.LG2025
A Scalable and Efficient Signal Integration System for Job Matching
Ping Liu, Rajat Arora, Xiao Shi +13
LinkedIn, one of the world's largest platforms for professional networking and job seeking, encounters various modeling challenges in building recommendation systems for its job ma…