1 citations · 2 across the 6 of their papers we have counts for
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cs.IR2024★ 1 cited
Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs
Chuang Zhao, Xing Su, Ming He +3
Owing to the impressive general intelligence of large language models (LLMs), there has been a growing trend to integrate them into recommender systems to gain a more profound insi…
cs.IR2024★ 1 cited
Cross-domain Transfer of Valence Preferences via a Meta-optimization Approach
Chuang Zhao, Hongke Zhao, Ming He +2
Cross-domain recommendation offers a potential avenue for alleviating data sparsity and cold-start problems. Embedding and mapping, as a classic cross-domain research genre, aims t…