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Dynamical Parameters: An Interpretability Framework for Time-Series Foundation Models

Yang, Kang et al.
arXiv (All) · Papers
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This work studies a central gap in interpreting time-series foundation models (TSFMs): a dynamical property may be accessible in a hidden state even when the forecast fails to respond correctly as that property changes. We formalize these properties as Dynamical Parameters, including trend slope, os
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