8 citations · 9 across the 5 of their papers we have counts for
Showing cs.IRShow all
2 papers · 1 filter
cs.IR2025
Graph Foundation Models for Recommendation: A Comprehensive Survey
Bin Wu, Yihang Wang, Yuanhao Zeng +7
Recommender systems (RS) serve as a fundamental tool for navigating the vast expanse of online information, with deep learning advancements playing an increasingly important role i…
cs.IR2024
Efficient Multi-task Prompt Tuning for Recommendation
Ting Bai, Le Huang, Yue Yu +4
With the expansion of business scenarios, real recommender systems are facing challenges in dealing with the constantly emerging new tasks in multi-task learning frameworks. In thi…