2 citations · 5 across the 4 of their papers we have counts for
4 papers
Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation
Ziyan Wang, Yingpeng Du, Zhu Sun +4
Large Language Models (LLMs) are emerging as promising approaches to enhance session-based recommendation (SBR), where both prompt-based and fine-tuning-based methods have been wid…
Large Language Model with Graph Convolution for Recommendation
Yingpeng Du, Ziyan Wang, Zhu Sun +6
In recent years, efforts have been made to use text information for better user profiling and item characterization in recommendations. However, text information can sometimes be o…
Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation
Wenxuan Zhang, Hongzhi Liu, Yingpeng Du +4
Generative large language models(LLMs) are proficient in solving general problems but often struggle to handle domain-specific tasks. This is because most of domain-specific tasks,…
Enhancing Job Recommendation through LLM-based Generative Adversarial Networks
Yingpeng Du, Di Luo, Rui Yan +4
Recommending suitable jobs to users is a critical task in online recruitment platforms, as it can enhance users' satisfaction and the platforms' profitability. While existing job r…