7 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…
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…
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…
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…
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…
MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation
Jialin Luo, Yuanzhi Wang, Ziqi Gu +7
Recently, the diffusion-based generative paradigm has achieved impressive general image generation capabilities with text prompts due to its accurate distribution modeling and stab…