2 papers
cs.IR2025
Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling
Heng Chang, Liang Gu, Cheng Hu +5
Cross-domain recommendation (CDR) is a task that aims to improve the recommendation performance in a target domain by leveraging the information from source domains. Contrastive le…
cs.IR2024
A Practice-Friendly LLM-Enhanced Paradigm with Preference Parsing for Sequential Recommendation
Dugang Liu, Shenxian Xian, Xiaolin Lin +5
The training paradigm integrating large language models (LLM) is gradually reshaping sequential recommender systems (SRS) and has shown promising results. However, most existing LL…