activity
20212026
most citedDeMod: A Holistic Tool with Explainable Detection and Personalized Modification for Toxicity Censorship

6 citations · 25 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

6 papers · 1 filter

cs.IR2024★ 1 cited

Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation

Jiafeng Xia, Dongsheng Li, Hansu Gu +4

Sequential recommendation methods can capture dynamic user preferences from user historical interactions to achieve better performance. However, most existing methods only use past…

cs.HC2024★ 6 cited

DeMod: A Holistic Tool with Explainable Detection and Personalized Modification for Toxicity Censorship

Yaqiong Li, Peng Zhang, Hansu Gu +5

Although there have been automated approaches and tools supporting toxicity censorship for social posts, most of them focus on detection. Toxicity censorship is a complex process,…

cs.IR2024★ 1 cited

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-…

cs.HC2024★ 5 cited

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,…

cs.IR2024

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…

cs.IR2024

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…