Leveraging multimodal large language model for multimodal sequential recommendation

Leveraging multimodal large language model for multimodal sequential recommendation

Abstract Multimodal large language models (MLLMs) have demonstrated remarkable superiority in various vision-language tasks due to their unparalleled cross-modal comprehension capabilities and extensive world knowledge, offering promising research paradigms to address the insufficient information ex...

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Bibliographic Details
Main Authors: Zhaoliang Wang, Baisong Liu, Weiming Huang, Tingting Hao, Huiqian Zhou, Yuxin Guo
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Recommender systems
Sequential recommendation
Multimodal recommendation
Multimodal large language model
Online Access:https://doi.org/10.1038/s41598-025-14251-1
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