9 citations · 24 across the 11 of their papers we have counts for
4 papers · 1 filter
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services
Wei Yuan, Chaoqun Yang, Guanhua Ye +3
Federated sequential recommendation (FedSeqRec) has gained growing attention due to its ability to protect user privacy. Unfortunately, the performance of FedSeqRec is still unsati…
PDC-FRS: Privacy-preserving Data Contribution for Federated Recommender System
Chaoqun Yang, Wei Yuan, Liang Qu +1
Federated recommender systems (FedRecs) have emerged as a popular research direction for protecting users' privacy in on-device recommendations. In FedRecs, users keep their data l…
PTF-FSR: A Parameter Transmission-Free Federated Sequential Recommender System
Wei Yuan, Chaoqun Yang, Liang Qu +3
Sequential recommender systems have made significant progress. Recently, due to increasing concerns about user data privacy, some researchers have implemented federated learning fo…
Robust Federated Contrastive Recommender System against Model Poisoning Attack
Wei Yuan, Chaoqun Yang, Liang Qu +3
Federated Recommender Systems (FedRecs) have garnered increasing attention recently, thanks to their privacy-preserving benefits. However, the decentralized and open characteristic…