4 citations · 13 across the 15 of their papers we have counts for
5 papers · 1 filter
Time-Aware Adaptive Side Information Fusion for Sequential Recommendation
Jie Luo, Wenyu Zhang, Xinming Zhang +1
Incorporating item-side information, such as category and brand, into sequential recommendation is a well-established and effective approach for improving performance. However, des…
Event-Aware Prompt Learning for Dynamic Graphs
Xingtong Yu, Ruijuan Liang, Renhe Jiang +4
Real-world graph typically evolve via a series of events, modeling dynamic interactions between objects across various domains. For dynamic graph learning, dynamic graph neural net…
MolGA: Molecular Graph Adaptation with Pre-trained 2D Graph Encoder
Xingtong Yu, Chang Zhou, Xinming Zhang +1
Molecular graph representation learning is widely used in chemical and biomedical research. While pre-trained 2D graph encoders have demonstrated strong performance, they overlook…
Bridging Domain Gaps between Pretrained Multimodal Models and Recommendations
Wenyu Zhang, Jie Luo, Xinming Zhang +1
With the explosive growth of multimodal content online, pre-trained visual-language models have shown great potential for multimodal recommendation. However, while these models ach…
GCoT: Chain-of-Thought Prompt Learning for Graphs
Xingtong Yu, Chang Zhou, Zhongwei Kuai +2
Chain-of-thought (CoT) prompting has achieved remarkable success in natural language processing (NLP). However, its vast potential remains largely unexplored for graphs. This raise…