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20242026
most citedTowards Edge General Intelligence via Large Language Models: Opportunities and Challenges

26 citations · 75 across the 30 of their papers we have counts for

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5 papers · 1 filter

cs.IR2024

Don't Lose Yourself: Boosting Multimodal Recommendation via Reducing Node-neighbor Discrepancy in Graph Convolutional Network

Zheyu Chen, Jinfeng Xu, Haibo Hu

The rapid expansion of multimedia contents has led to the emergence of multimodal recommendation systems. It has attracted increasing attention in recommendation systems because it…

cs.DC2024★ 26 cited

Towards Edge General Intelligence via Large Language Models: Opportunities and Challenges

Handi Chen, Weipeng Deng, Shuo Yang +5

Edge Intelligence (EI) has been instrumental in delivering real-time, localized services by leveraging the computational capabilities of edge networks. The integration of Large Lan…

cs.IR2024★ 21 cited

AlignGroup: Learning and Aligning Group Consensus with Member Preferences for Group Recommendation

Jinfeng Xu, Zheyu Chen, Jinze Li +3

Group activities are important behaviors in human society, providing personalized recommendations for groups is referred to as the group recommendation task. Existing methods can u…

cs.IR2024★ 23 cited

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…

cs.IR2024★ 2 cited

MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation

Jinfeng Xu, Zheyu Chen, Shuo Yang +3

With the increasing multimedia information, multimodal recommendation has received extensive attention. It utilizes multimodal information to alleviate the data sparsity problem in…