24 citations · 39 across the 6 of their papers we have counts for
6 papers
Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback
Weizhi Zhang, Wooseong Yang, Yuxin Cui +9
Traditional recommender systems (RecSys) primarily infer user preferences from implicit signals (such as clicks, watches, and purchases), often neglecting the rich explicit context…
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection
Ronghui Xu, Hao Miao, Senzhang Wang +2
With the proliferation of mobile sensing techniques, huge amounts of time series data are generated and accumulated in various domains, fueling plenty of real-world applications. I…
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju, Siyu Yi, Yifan Wang +10
Graph-structured data exhibits universality and widespread applicability across diverse domains, such as social network analysis, biochemistry, financial fraud detection, and netwo…
Large Language Model Simulator for Cold-Start Recommendation
Feiran Huang, Yuanchen Bei, Zhenghang Yang +6
Recommending cold items remains a significant challenge in billion-scale online recommendation systems. While warm items benefit from historical user behaviors, cold items rely sol…
Interpretable and Effective Reinforcement Learning for Attacking against Graph-based Rumor Detection
Yuefei Lyu, Xiaoyu Yang, Jiaxin Liu +3
Social networks are frequently polluted by rumors, which can be detected by advanced models such as graph neural networks. However, the models are vulnerable to attacks and underst…
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation with Pre-training
Juyong Jiang, Peiyan Zhang, Yingtao Luo +6
Sequential recommendation systems are integral to discerning temporal user preferences. Yet, the task of learning from abbreviated user interaction sequences poses a notable challe…