Correcting False Alarms from Unseen: Adapting Graph Anomaly Detectors at Test Time
Fuente:
arXiv
Guardado en:
| Autores principales: | Pan, Junjun, Liu, Yixin, Zhou, Chuan, Xiong, Fei, Liew, Alan Wee-Chung, Pan, Shirui |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection
por: Pan, Junjun, et al.
Publicado: (2026)
por: Pan, Junjun, et al.
Publicado: (2026)
Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
por: Liu, Yujing, et al.
Publicado: (2026)
por: Liu, Yujing, et al.
Publicado: (2026)
A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection
por: Pan, Junjun, et al.
Publicado: (2025)
por: Pan, Junjun, et al.
Publicado: (2025)
ARC: A Generalist Graph Anomaly Detector with In-Context Learning
por: Liu, Yixin, et al.
Publicado: (2024)
por: Liu, Yixin, et al.
Publicado: (2024)
A Survey of Generalization of Graph Anomaly Detection: From Transfer Learning to Foundation Models
por: Pan, Junjun, et al.
Publicado: (2025)
por: Pan, Junjun, et al.
Publicado: (2025)
Explainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection
por: Pan, Junjun, et al.
Publicado: (2025)
por: Pan, Junjun, et al.
Publicado: (2025)
FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection
por: Zhao, Yunfeng, et al.
Publicado: (2026)
por: Zhao, Yunfeng, et al.
Publicado: (2026)
FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection
por: Zhao, Yunfeng, et al.
Publicado: (2025)
por: Zhao, Yunfeng, et al.
Publicado: (2025)
From Few-Shot to Zero-Shot: Towards Generalist Graph Anomaly Detection
por: Liu, Yixin, et al.
Publicado: (2026)
por: Liu, Yixin, et al.
Publicado: (2026)
Beyond a Single Perspective: Text Anomaly Detection with Multi-View Language Representations
por: Liu, Yixin, et al.
Publicado: (2026)
por: Liu, Yixin, et al.
Publicado: (2026)
Towards One-for-All Anomaly Detection for Tabular Data
por: Li, Shiyuan, et al.
Publicado: (2026)
por: Li, Shiyuan, et al.
Publicado: (2026)
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
por: Wang, Yili, et al.
Publicado: (2024)
por: Wang, Yili, et al.
Publicado: (2024)
Reasoning over User Preferences: Knowledge Graph-Augmented LLMs for Explainable Conversational Recommendations
por: Qiu, Zhangchi, et al.
Publicado: (2024)
por: Qiu, Zhangchi, et al.
Publicado: (2024)
Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender Systems
por: Qiu, Zhangchi, et al.
Publicado: (2023)
por: Qiu, Zhangchi, et al.
Publicado: (2023)
Out-of-Distribution Detection on Graphs: A Survey
por: Cai, Tingyi, et al.
Publicado: (2025)
por: Cai, Tingyi, et al.
Publicado: (2025)
Decision-focused Graph Neural Networks for Combinatorial Optimization
por: Liu, Yang, et al.
Publicado: (2024)
por: Liu, Yang, et al.
Publicado: (2024)
GOODAT: Towards Test-time Graph Out-of-Distribution Detection
por: Wang, Luzhi, et al.
Publicado: (2024)
por: Wang, Luzhi, et al.
Publicado: (2024)
Test-time GNN Model Evaluation on Dynamic Graphs
por: Li, Bo, et al.
Publicado: (2025)
por: Li, Bo, et al.
Publicado: (2025)
Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation
por: Li, Shiyuan, et al.
Publicado: (2024)
por: Li, Shiyuan, et al.
Publicado: (2024)
Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach
por: Chen, Qingfeng, et al.
Publicado: (2025)
por: Chen, Qingfeng, et al.
Publicado: (2025)
Online GNN Evaluation Under Test-time Graph Distribution Shifts
por: Zheng, Xin, et al.
Publicado: (2024)
por: Zheng, Xin, et al.
Publicado: (2024)
Graph Neural Networks for Graphs with Heterophily: A Survey
por: Zheng, Xin, et al.
Publicado: (2022)
por: Zheng, Xin, et al.
Publicado: (2022)
Graph Retrieval-Augmented LLM for Conversational Recommendation Systems
por: Qiu, Zhangchi, et al.
Publicado: (2025)
por: Qiu, Zhangchi, et al.
Publicado: (2025)
Evaluating False Alarm and Missing Attacks in CAN IDS
por: Hossain, Nirab, et al.
Publicado: (2026)
por: Hossain, Nirab, et al.
Publicado: (2026)
Deep Learning for Time Series Anomaly Detection: A Survey
por: Darban, Zahra Zamanzadeh, et al.
Publicado: (2022)
por: Darban, Zahra Zamanzadeh, et al.
Publicado: (2022)
SigmaMedStat: Temporal Signal Modeling for ICU False Alarm Reduction
por: Ramachandran, Arunkumar
Publicado: (2026)
por: Ramachandran, Arunkumar
Publicado: (2026)
Variational Bayesian Flow Network for Graph Generation
por: Xiong, Yida, et al.
Publicado: (2026)
por: Xiong, Yida, et al.
Publicado: (2026)
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
por: Jin, Ming, et al.
Publicado: (2023)
por: Jin, Ming, et al.
Publicado: (2023)
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
por: Zhang, He, et al.
Publicado: (2023)
por: Zhang, He, et al.
Publicado: (2023)
Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values
por: Zheng, Yu, et al.
Publicado: (2024)
por: Zheng, Yu, et al.
Publicado: (2024)
Periodic Graph-Enhanced Multivariate Time Series Anomaly Detector
por: Li, Jia, et al.
Publicado: (2025)
por: Li, Jia, et al.
Publicado: (2025)
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
por: Pan, Sheng, et al.
Publicado: (2026)
por: Pan, Sheng, et al.
Publicado: (2026)
OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories
por: Li, Bo, et al.
Publicado: (2025)
por: Li, Bo, et al.
Publicado: (2025)
Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models
por: Shen, Xu, et al.
Publicado: (2024)
por: Shen, Xu, et al.
Publicado: (2024)
OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models
por: Li, Shiyuan, et al.
Publicado: (2026)
por: Li, Shiyuan, et al.
Publicado: (2026)
Tabular Foundation Models are Strong Graph Anomaly Detectors
por: Liu, Yunhui, et al.
Publicado: (2026)
por: Liu, Yunhui, et al.
Publicado: (2026)
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection
por: Darban, Zahra Zamanzadeh, et al.
Publicado: (2023)
por: Darban, Zahra Zamanzadeh, et al.
Publicado: (2023)
Finite-Horizon Quickest Change Detection Balancing Latency with False Alarm Probability
por: Huang, Yu-Han, et al.
Publicado: (2025)
por: Huang, Yu-Han, et al.
Publicado: (2025)
Structural Alignment Improves Graph Test-Time Adaptation
por: Hsu, Hans Hao-Hsun, et al.
Publicado: (2025)
por: Hsu, Hans Hao-Hsun, et al.
Publicado: (2025)
Multi-modal Multi-kernel Graph Learning for Autism Prediction and Biomarker Discovery
por: Liu, Jin, et al.
Publicado: (2023)
por: Liu, Jin, et al.
Publicado: (2023)
Ejemplares similares
-
CAMERA: Adapting to Semantic Camouflage in Unsupervised Text-Attributed Graph Fraud Detection
por: Pan, Junjun, et al.
Publicado: (2026) -
Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
por: Liu, Yujing, et al.
Publicado: (2026) -
A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection
por: Pan, Junjun, et al.
Publicado: (2025) -
ARC: A Generalist Graph Anomaly Detector with In-Context Learning
por: Liu, Yixin, et al.
Publicado: (2024) -
A Survey of Generalization of Graph Anomaly Detection: From Transfer Learning to Foundation Models
por: Pan, Junjun, et al.
Publicado: (2025)