23 citations · 26 across the 7 of their papers we have counts for
5 papers · 1 filter
Agents as Knowledge Integrator and Utilizer in Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +9
Online platforms increasingly rely on multimodal recommender systems to rank products, media, and other Web content. Existing methods usually inject visual and textual features int…
Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Recent advancements in multimodal recommendations, which leverage diverse modality information to mitigate data sparsity and improve recommendation accuracy, have gained significan…
COHESION: Composite Graph Convolutional Network with Dual-Stage Fusion for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Wei Wang +3
Recent works in multimodal recommendations, which leverage diverse modal information to address data sparsity and enhance recommendation accuracy, have garnered considerable intere…
A Survey on Multimodal Recommender Systems: Recent Advances and Future Directions
Jinfeng Xu, Zheyu Chen, Shuo Yang +5
Acquiring valuable data from the rapidly expanding information on the internet has become a significant concern, and recommender systems have emerged as a widely used and effective…
Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
Jinfeng Xu, Zheyu Chen, Jinze Li +4
Graph Collaborative Filtering (GCF) has emerged as a dominant paradigm in modern recommendation systems, excelling at modeling complex user-item interactions and capturing high-ord…