65 citations · 232 across the 23 of their papers we have counts for
6 papers · 1 filter
Filtering Discomforting Recommendations with Large Language Models
Jiahao Liu, Yiyang Shao, Peng Zhang +6
Personalized algorithms can inadvertently expose users to discomforting recommendations, potentially triggering negative consequences. The subjectivity of discomfort and the black-…
GraphTransfer: A Generic Feature Fusion Framework for Collaborative Filtering
Jiafeng Xia, Dongsheng Li, Hansu Gu +2
Graph Neural Networks (GNNs) have demonstrated effectiveness in collaborative filtering tasks due to their ability to extract powerful structural features. However, combining the g…
Role Identification based Method for Cyberbullying Analysis in Social Edge Computing
Runyu Wang, Tun Lu, Peng Zhang +1
Over the past few years, many efforts have been dedicated to studying cyberbullying in social edge computing devices, and most of them focus on three roles: victims, perpetrators,…
AOTree: Aspect Order Tree-based Model for Explainable Recommendation
Wenxin Zhao, Peng Zhang, Hansu Gu +3
Recent recommender systems aim to provide not only accurate recommendations but also explanations that help users understand them better. However, most existing explainable recomme…
Negating Negatives: Alignment with Human Negative Samples via Distributional Dispreference Optimization
Shitong Duan, Xiaoyuan Yi, Peng Zhang +5
Large language models (LLMs) have revolutionized the role of AI, yet pose potential social risks. To steer LLMs towards human preference, alignment technologies have been introduce…
Frequency-aware Graph Signal Processing for Collaborative Filtering
Jiafeng Xia, Dongsheng Li, Hansu Gu +4
Graph Signal Processing (GSP) based recommendation algorithms have recently attracted lots of attention due to its high efficiency. However, these methods failed to consider the im…