4 papers
A Hierarchical Quantized Tokenization Framework for Task-Adaptive Graph Representation Learning
Yang Xiang, Li Fan, Chenke Yin +2
Foundation models in language and vision benefit from a unified discrete token interface that converts raw inputs into sequences for scalable pre-training and inference. For graphs…
Dual prototype attentive graph network for cross-market recommendation
Li Fan, Menglin Kong, Yang Xiang +2
Cross-market recommender systems (CMRS) aim to utilize historical data from mature markets to promote multinational products in emerging markets. However, existing CMRS approaches…
Harnessing Light for Cold-Start Recommendations: Leveraging Epistemic Uncertainty to Enhance Performance in User-Item Interactions
Yang Xiang, Li Fan, Chenke Yin +2
Most recent paradigms of generative model-based recommendation still face challenges related to the cold-start problem. Existing models addressing cold item recommendations mainly…
RDSA: A Robust Deep Graph Clustering Framework via Dual Soft Assignment
Yang Xiang, Li Fan, Tulika Saha +4
Graph clustering is an essential aspect of network analysis that involves grouping nodes into separate clusters. Recent developments in deep learning have resulted in graph cluster…