4 citations · 9 across the 12 of their papers we have counts for
Showing cs.IRShow all
2 papers · 1 filter
cs.IR2025
Non-parametric Graph Convolution for Re-ranking in Recommendation Systems
Zhongyu Ouyang, Mingxuan Ju, Soroush Vosoughi +1
Graph knowledge has been proven effective in enhancing item rankings in recommender systems (RecSys), particularly during the retrieval stage. However, its application in the ranki…
cs.IR2025
What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context
Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang +2
What enables large language models (LLMs) to effectively model user preferences in sequential recommendation? Our investigation reveals that existing preference-alignment approache…