most citedTriple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.IR2024★ 2 cited

Triple Modality Fusion: Aligning Visual, Textual, and Graph Data with Large Language Models for Multi-Behavior Recommendations

Luyi Ma, Xiaohan Li, Zezhong Fan +7

Integrating diverse data modalities is crucial for enhancing the performance of personalized recommendation systems. Traditional models, which often rely on singular data sources,…