1 citations · 1 across the 9 of their papers we have counts for
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MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning
Ahmad Mousavi, Majid Alikhani, Yeon-Chang Lee +2
Multimodal Graph Neural Networks have become standard for recommendation by augmenting sparse interaction data with content features. Yet current architectures face two bottlenecks…
Anchored Alignment: Preventing Positional Collapse in Multimodal Recommender Systems
Yonghun Jeong, David Yoon Suk Kang, Yeon-Chang Lee
Multimodal recommender systems (MMRS) leverage images, text, and interaction signals to enrich item representations. However, recent alignment based MMRSs that enforce a unified em…
Embedding-aware Polarization Management in Signed Networks
Jeonghan Son, Kyungsik Han, Yeon-Chang Lee
Signed network embeddings (SNE) are widely used to represent networks with positive and negative relations, but their repeated use in downstream analysis pipelines can inadvertentl…
E-MMKGR: A Unified Multimodal Knowledge Graph Framework for E-commerce Applications
Jiwoo Kang, Yeon-Chang Lee
Multimodal recommender systems (MMRSs) enhance collaborative filtering by leveraging item-side modalities, but their reliance on a fixed set of modalities and task-specific objecti…
Improving the Accuracy of Community Detection on Signed Networks via Community Refinement and Contrastive Learning
Hyunuk Shin, Hojin Kim, Chanyoung Lee +2
Community detection (CD) on signed networks is crucial for understanding how positive and negative relations jointly shape network structure. However, existing CD methods often yie…