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cs.IR2025
Large Language Model Enhanced Graph Invariant Contrastive Learning for Out-of-Distribution Recommendation
Jiahao Liang, Haoran Yang, Xiangyu Zhao +4
Out-of-distribution (OOD) generalization has emerged as a significant challenge in graph recommender systems. Traditional graph neural network algorithms often fail because they le…
cs.IR2025
Democratic Recommendation with User and Item Representatives Produced by Graph Condensation
Jiahao Liang, Haoran Yang, Xiangyu Zhao +4
The challenges associated with large-scale user-item interaction graphs have attracted increasing attention in graph-based recommendation systems, primarily due to computational in…