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

arXiv:2609.34316 · cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Terminology

• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Interpretability — 1× in this paper · explained in 15 episodes

Sources

• Chronos-2: From Univariate to Universal Forecasting
• Universal Redundancies in Time Series Foundation Models
• Aionoscope: Debugging Latent-State Accessibility in Time-Series Representations
• Learnable Koopman-Enhanced Transformer-Based Time Series Forecasting with Spectral Control
• TimeGPT-1
• Causal Analysis for Time Series Foundation Models
• Dissecting Chronos: Sparse Autoencoders Reveal Causal Feature Hierarchies in Time Series Foundation Models
• On the Internal Semantics of Time-Series Foundation Models
• Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
• time2time: Causal Intervention in Hidden States to Simulate Rare Events in Time Series Foundation Models
• EIDOS: Latent-Space Predictive Learning for Time Series Foundation Models

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