A comprehensive survey on multimodal recommender systems: Taxonomy, evaluation, and future directions
Recommendation systems have become popular and effective tools to help users discover
their interesting items by modeling the user preference and item property based on implicit …
their interesting items by modeling the user preference and item property based on implicit …
Lightgt: A light graph transformer for multimedia recommendation
Multimedia recommendation methods aim to discover the user preference on the multi-
modal information to enhance the collaborative filtering (CF) based recommender system …
modal information to enhance the collaborative filtering (CF) based recommender system …
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 …
Multimodal graph contrastive learning for multimedia-based recommendation
Multimedia-based recommendation is a challenging task that requires not only learning
collaborative signals from user-item interaction, but also capturing modality-specific user …
collaborative signals from user-item interaction, but also capturing modality-specific user …
Dynamic multimodal fusion via meta-learning towards micro-video recommendation
Multimodal information (eg, visual, acoustic, and textual) has been widely used to enhance
representation learning for micro-video recommendation. For integrating multimodal …
representation learning for micro-video recommendation. For integrating multimodal …
Equivariant Learning for Out-of-Distribution Cold-start Recommendation
Recommender systems rely on user-item interactions to learn Collaborative Filtering (CF)
signals and easily under-recommend the cold-start items without historical interactions. To …
signals and easily under-recommend the cold-start items without historical interactions. To …
Multimodal recommender systems: A survey
The recommender system (RS) has been an integral toolkit of online services. They are
equipped with various deep learning techniques to model user preference based on …
equipped with various deep learning techniques to model user preference based on …
Promptmm: Multi-modal knowledge distillation for recommendation with prompt-tuning
Multimedia online platforms (eg, Amazon, TikTok) have greatly benefited from the
incorporation of multimedia (eg, visual, textual, and acoustic) content into their personal …
incorporation of multimedia (eg, visual, textual, and acoustic) content into their personal …
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 …
Knowledge-enhanced causal reinforcement learning model for interactive recommendation
Owing to its inherently dynamic nature and economical training cost, offline reinforcement
learning (RL) is typically employed to implement an interactive recommender system (IRS) …
learning (RL) is typically employed to implement an interactive recommender system (IRS) …