128 citations · 355 across the 13 of their papers we have counts for
13 papers
On the User Behavior Leakage from Recommender System Exposure
Xin Xin, Jiyuan Yang, Hanbing Wang +6
Modern recommender systems are trained to predict users potential future interactions from users historical behavior data. During the interaction process, despite the data coming f…
Improving Transformer-based Sequential Recommenders through Preference Editing
Muyang Ma, Pengjie Ren, Zhumin Chen +4
One of the key challenges in Sequential Recommendation (SR) is how to extract and represent user preferences. Traditional SR methods rely on the next item as the supervision signal…
Semi-Supervised Variational Reasoning for Medical Dialogue Generation
Dongdong Li, Zhaochun Ren, Pengjie Ren +4
Medical dialogue generation aims to provide automatic and accurate responses to assist physicians to obtain diagnosis and treatment suggestions in an efficient manner. In medical d…
A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation
Minghong Xu, Piji Li, Haoran Yang +4
Unstructured Persona-oriented Dialogue Systems (UPDS) has been demonstrated effective in generating persona consistent responses by utilizing predefined natural language user perso…
Meta Matrix Factorization for Federated Rating Predictions
Yujie Lin, Pengjie Ren, Zhumin Chen +5
Federated recommender systems have distinct advantages in terms of privacy protection over traditional recommender systems that are centralized at a data center. However, previous…
Parallel Split-Join Networks for Shared-account Cross-domain Sequential Recommendations
Wenchao Sun, Muyang Ma, Pengjie Ren +5
Sequential recommendation is a task in which one models and uses sequential information about user behavior for recommendation purposes. We study sequential recommendation in a par…