3 papers
cs.CL2025
LANTERN: Scalable Distillation of Large Language Models for Job-Person Fit and Explanation
Zhoutong Fu, Yihan Cao, Yi-Lin Chen +16
Large language models (LLMs) have achieved strong performance across a wide range of natural language processing tasks. However, deploying LLMs at scale for domain specific applica…
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…