AI RESEARCH
INTARG: Informed Real-Time Adversarial Attack Generation for Time-Series Regression
arXiv CS.LG
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ArXi:2604.11928v1 Announce Type: new Time-series forecasting aims to predict future values by modeling temporal dependencies in historical observations. It is a critical component of many real-world systems, where accurate forecasts improve operational efficiency and help mitigate uncertainty and risk. recently, machine learning (ML), and especially deep learning (DL)-based models, have gained widespread adoption for time-series forecasting, but they remain vulnerable to adversarial attacks.