PEARL: A dual-layer graph learning for multimodal recommendation

Yuzhuo Dang, Wanyu Chen, Zhiqiang Pan, Yuxiao Duan, Fei Cai, Honghui Chen

Abstract: Highlights•Enhancing multimodal recommendation through a dual-layer graph learning framework.•Eliminating the noise caused by the user’s imbalanced attention for the first time.•Mining the intra-modal self-supervised signals through the affinity graph learning.•Introducing an augmentation-free contrastive learning task based on modal attributes.•Sufficient experimental results on three datasets verify the superiority of PEARL.