12 citations · 13 across the 5 of their papers we have counts for
3 papers · 2 filters
Prompt Tuning for Item Cold-start Recommendation
Yuezihan Jiang, Gaode Chen, Wenhan Zhang +6
The item cold-start problem is crucial for online recommender systems, as the success of the cold-start phase determines whether items can transition into popular ones. Prompt lear…
Online Item Cold-Start Recommendation with Popularity-Aware Meta-Learning
Yunze Luo, Yuezihan Jiang, Yinjie Jiang +5
With the rise of e-commerce and short videos, online recommender systems that can capture users' interests and update new items in real-time play an increasingly important role. In…
A Unified Framework for Cross-Domain Recommendation
Jiangxia Cao, Shen Wang, Gaode Chen +4
In addressing the persistent challenges of data-sparsity and cold-start issues in domain-expert recommender systems, Cross-Domain Recommendation (CDR) emerges as a promising method…