2 papers
cs.LG2026
Trinity: A Scenario-Aware Recommendation Framework for Large-Scale Cold-Start Users
Wenhao Zheng, Wang Lu, Fangshuang Tang +4
Early-stage users in a new scenario intensify cold-start challenges, yet prior works often address only parts of the problem through model architecture. Launching a new user experi…
cs.CL2026
Learning User Interests via Reasoning and Distillation for Cross-Domain News Recommendation
Mengdan Zhu, Yufan Zhao, Tao Di +2
News recommendation plays a critical role in online news platforms by helping users discover relevant content. Cross-domain news recommendation further requires inferring user's un…