2 citations · 2 across the 5 of their papers we have counts for
5 papers
Slow Thinking for Sequential Recommendation
Junjie Zhang, Beichen Zhang, Wenqi Sun +4
To develop effective sequential recommender systems, numerous methods have been proposed to model historical user behaviors. Despite the effectiveness, these methods share the same…
Curriculum-scheduled Knowledge Distillation from Multiple Pre-trained Teachers for Multi-domain Sequential Recommendation
Wenqi Sun, Ruobing Xie, Junjie Zhang +3
Pre-trained recommendation models (PRMs) have received increasing interest recently. However, their intrinsically heterogeneous model structure, huge model size and computation cos…
Universal Multi-modal Multi-domain Pre-trained Recommendation
Wenqi Sun, Ruobing Xie, Shuqing Bian +2
There is a rapidly-growing research interest in modeling user preferences via pre-training multi-domain interactions for recommender systems. However, Existing pre-trained multi-do…
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems
Junjie Zhang, Yupeng Hou, Ruobing Xie +5
Recently, there has been an emergence of employing LLM-powered agents as believable human proxies, based on their remarkable decision-making capability. However, existing studies m…
RecBole 2.0: Towards a More Up-to-Date Recommendation Library
Wayne Xin Zhao, Yupeng Hou, Xingyu Pan +16
In order to support the study of recent advances in recommender systems, this paper presents an extended recommendation library consisting of eight packages for up-to-date topics a…