MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning
Multimodal Graph Neural Networks have become standard for recommendation by augmenting sparse interaction data with content features. Yet current architectures face two bottlenecks: structural rigidity, from a reliance on static precomputed similarity graphs that cannot adapt to evolving preferences; and semantic fragility, where noisy modality signals are indiscriminately fused, distorting the collaborative signal. We propose MURAL (Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning), a unified framework that shifts multimodal recommendation from fixed structural augmentation to dynamic topology discovery. To address structural rigidity, an Adaptive Edge Learner combi...
| Authors | Ahmad Mousavi, Majid Alikhani, Yeon-Chang Lee et al. |
|---|---|
| Primary category | cs.IR |
| Published | 4 September 2026 |
| Last updated at source | 4 September 2026 |
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