Online distillation-enhanced multi-modal transformer for sequential recommendation
Multi-modal recommendation systems, which integrate diverse types of information, have
gained widespread attention in recent years. However, compared to traditional collaborative …
gained widespread attention in recent years. However, compared to traditional collaborative …
Leveraging multimodal features and item-level user feedback for bundle construction
Automatic bundle construction is a crucial prerequisite step in various bundle-aware online
services. Previous approaches are mostly designed to model the bundling strategy of …
services. Previous approaches are mostly designed to model the bundling strategy of …
Large multi-modal encoders for recommendation
In recent years, the rapid growth of online multimedia services, such as e-commerce
platforms, has necessitated the development of personalised recommendation approaches …
platforms, has necessitated the development of personalised recommendation approaches …
Semantic-Guided Feature Distillation for Multimodal Recommendation
Multimodal recommendation exploits the rich multimodal information associated with users
or items to enhance the representation learning for better performance. In these methods …
or items to enhance the representation learning for better performance. In these methods …
MMGRec: Multimodal Generative Recommendation with Transformer Model
Multimodal recommendation aims to recommend user-preferred candidates based on
her/his historically interacted items and associated multimodal information. Previous studies …
her/his historically interacted items and associated multimodal information. Previous studies …
FMMRec: Fairness-aware Multimodal Recommendation
Recently, multimodal recommendations have gained increasing attention for effectively
addressing the data sparsity problem by incorporating modality-based representations …
addressing the data sparsity problem by incorporating modality-based representations …
Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey
Personalized recommendation serves as a ubiquitous channel for users to discover
information or items tailored to their interests. However, traditional recommendation models …
information or items tailored to their interests. However, traditional recommendation models …
Attribute-driven Disentangled Representation Learning for Multimodal Recommendation
Recommendation algorithms forecast user preferences by correlating user and item
representations derived from historical interaction patterns. In pursuit of enhanced …
representations derived from historical interaction patterns. In pursuit of enhanced …
PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation
To help merchants/customers to provide/access a variety of services through miniapps,
online service platforms have occupied a critical position in the effective content delivery, in …
online service platforms have occupied a critical position in the effective content delivery, in …
Collaborative Denoised Graph Contrastive Learning for Multi-modal Recommendation
F Xu, Z Zhu, Y Fu, P Liu - Information Sciences, 2024 - Elsevier
Graph neural networks, with their capacity to capture complex hierarchical relations, are
extensively employed in multi-modal recommendation. Previous graph-based multi-modal …
extensively employed in multi-modal recommendation. Previous graph-based multi-modal …