22 citations · 24 across the 3 of their papers we have counts for
3 papers
cs.IR2025
Federated Cross-Domain Click-Through Rate Prediction With Large Language Model Augmentation
Jiangcheng Qin, Xueyuan Zhang, Baisong Liu +2
Accurately predicting click-through rates (CTR) under stringent privacy constraints poses profound challenges, particularly when user-item interactions are sparse and fragmented ac…
cs.IR2022★ 22 cited
Split Two-Tower Model for Efficient and Privacy-Preserving Cross-device Federated Recommendation
Jiangcheng Qin, Baisong Liu, Xueyuan Zhang +1
Federated Recommendation can mitigate the systematical privacy risks of traditional recommendation since it allows the model training and online inferring without centralized user…
cs.IR2020★ 2 cited
A Novel Privacy-Preserved Recommender System Framework based on Federated Learning
Jiangcheng Qin, Baisong Liu
Recommender System (RS) is currently an effective way to solve information overload. To meet users' next click behavior, RS needs to collect users' personal information and behavio…