2 citations · 2 across the 5 of their papers we have counts for
5 papers
ProMax: Exploring the Potential of LLM-derived Profiles with Distribution Shaping for Recommender Systems
Yi Zhang, Yiwen Zhang, Kai Zheng +2
The remarkable text understanding and generation capabilities of large language models (LLMs) have revitalized the field of general recommendation based on implicit user feedback.…
Diversity-aware Dual-promotion Poisoning Attack on Sequential Recommendation
Yuchuan Zhao, Tong Chen, Junliang Yu +3
Sequential recommender systems (SRSs) excel in capturing users' dynamic interests, thus playing a key role in various industrial applications. The popularity of SRSs has also drive…
On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective
Hung Vinh Tran, Tong Chen, Guanhua Ye +3
Content-based Recommender Systems (CRSs) play a crucial role in shaping user experiences in e-commerce, online advertising, and personalized recommendations. However, due to the va…
Poisoning Decentralized Collaborative Recommender System and Its Countermeasures
Ruiqi Zheng, Liang Qu, Tong Chen +3
To make room for privacy and efficiency, the deployment of many recommender systems is experiencing a shift from central servers to personal devices, where the federated recommende…
Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation
Jing Long, Tong Chen, Guanhua Ye +3
As an indispensable personalized service within Location-Based Social Networks (LBSNs), the Point-of-Interest (POI) recommendation aims to assist individuals in discovering attract…