2 papers
cs.IR2026
When Recommendation Denoising Meets Popularity Bias: Understanding and Mitigating Their Interaction
Guohang Zeng, Jie Lu, Guangquan Zhang
Implicit feedback is the dominant data source for recommender systems, but behavioral logs are often contaminated by false-positive interactions caused by mis-clicks, biased exposu…
cs.IR2024
Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users
Guohang Zeng, Qian Zhang, Guangquan Zhang +1
Cross-Domain Recommendation (CDR) is a promising paradigm inspired by transfer learning to solve the cold-start problem in recommender systems. Existing state-of-the-art CDR method…