3 papers
cs.LG2026
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
Sheng Pan, Ming Jin, Bo Du +1
Time series forecasting serves as an essential tool for many real-world applications, supporting tasks such as resource optimization and decision-making. Despite significant archit…
cs.LG2026
FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection
Yunfeng Zhao, Yixin Liu, Qingfeng Chen +3
Graph-level anomaly detection (GLAD) is crucial for ensuring the reliability of graph-driven applications by identifying abnormal graphs that deviate from the majority. Considering…
cs.CR2026
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety
Xingjun Ma, Yifeng Gao, Yixu Wang +45
The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…