10 citations · 29 across the 6 of their papers we have counts for
6 papers
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
Wei Yuan, Quoc Viet Hung Nguyen, Tieke He +2
Federated Recommender Systems (FedRecs) are considered privacy-preserving techniques to collaboratively learn a recommendation model without sharing user data. Since all participan…
Interaction-level Membership Inference Attack Against Federated Recommender Systems
Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen +3
The marriage of federated learning and recommender system (FedRec) has been widely used to address the growing data privacy concerns in personalized recommendation services. In Fed…
APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models
Quanjun Zhang, Chunrong Fang, Weisong Sun +4
Automated program repair (APR) aims to fix software bugs automatically without human debugging efforts and plays a crucial role in software development and maintenance. Despite pro…
Federated Unlearning for On-Device Recommendation
Wei Yuan, Hongzhi Yin, Fangzhao Wu +3
The increasing data privacy concerns in recommendation systems have made federated recommendations (FedRecs) attract more and more attention. Existing FedRecs mainly focus on how t…
CIRCLE: Continual Repair across Programming Languages
Wei Yuan, Quanjun Zhang, Tieke He +4
Automatic Program Repair (APR) aims at fixing buggy source code with less manual debugging efforts, which plays a vital role in improving software reliability and development produ…
Unified Question Generation with Continual Lifelong Learning
Wei Yuan, Hongzhi Yin, Tieke He +3
Question Generation (QG), as a challenging Natural Language Processing task, aims at generating questions based on given answers and context. Existing QG methods mainly focus on bu…