9 citations · 10 across the 8 of their papers we have counts for
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cs.IR2024
The 1st Workshop on Human-Centered Recommender Systems
Kaike Zhang, Yunfan Wu, Yougang lyu +6
Recommender systems are quintessential applications of human-computer interaction. Widely utilized in daily life, they offer significant convenience but also present numerous chall…
cs.CR2024★ 9 cited
FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement
Dezhong Yao, Tongtong Liu, Qi Cao +1
Federated Learning (FL) has emerged as a promising approach for preserving data privacy in recommendation systems by training models locally. Recently, Graph Neural Networks (GNN)…
cs.IR2024★ 1 cited
LoRec: Large Language Model for Robust Sequential Recommendation against Poisoning Attacks
Kaike Zhang, Qi Cao, Yunfan Wu +3
Sequential recommender systems stand out for their ability to capture users' dynamic interests and the patterns of item-to-item transitions. However, the inherent openness of seque…