13 citations · 13 across the 6 of their papers we have counts for
6 papers
Anomaly-Preference Image Generation
Fuyun Wang, Yuanzhi Wang, Xu Guo +6
Synthesizing realistic and diverse anomalous samples from limited data is vital for robust model generalization. However, existing methods struggle to reconcile fidelity and divers…
Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
Fuyun Wang, Yuanzhi Wang, Xu Guo +6
Open-set supervised anomaly detection (OSAD) aims to identify unseen anomalies using limited anomalous supervision. However, existing prototype-based methods typically model normal…
MMHCL: Multi-Modal Hypergraph Contrastive Learning for Recommendation
Xu Guo, Tong Zhang, Fuyun Wang +4
The burgeoning presence of multimodal content-sharing platforms propels the development of personalized recommender systems. Previous works usually suffer from data sparsity and co…
Multi-Modal Hypergraph Enhanced LLM Learning for Recommendation
Xu Guo, Tong Zhang, Yuanzhi Wang +6
The burgeoning presence of Large Language Models (LLM) is propelling the development of personalized recommender systems. Most existing LLM-based methods fail to sufficiently explo…
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection
Fuyun Wang, Tong Zhang, Yuanzhi Wang +4
In Open-set Supervised Anomaly Detection (OSAD), the existing methods typically generate pseudo anomalies to compensate for the scarcity of observed anomaly samples, while overlook…
Gradient based Feature Attribution in Explainable AI: A Technical Review
Yongjie Wang, Tong Zhang, Xu Guo +1
The surge in black-box AI models has prompted the need to explain the internal mechanism and justify their reliability, especially in high-stakes applications, such as healthcare a…