3 citations · 9 across the 6 of their papers we have counts for
6 papers
Multi-Normal Prototypes Learning for Weakly Supervised Anomaly Detection
Zhijin Dong, Hongzhi Liu, Boyuan Ren +2
Anomaly detection is a crucial task in various domains. Most of the existing methods assume the normal sample data clusters around a single central prototype while the real data ma…
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…
Relation-Aware Neighborhood Matching Model for Entity Alignment
Yao Zhu, Hongzhi Liu, Zhonghai Wu +1
Entity alignment which aims at linking entities with the same meaning from different knowledge graphs (KGs) is a vital step for knowledge fusion. Existing research focused on learn…
Android Multi-Level System Permission Management Approach
Yang Luo, Qixun Zhang, Qingni Shen +2
With the expansion of the market share occupied by the Android platform, security issues (especially application security) have become attention focus of researchers. In fact, the…