Author

L. Tran

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Preprint Aug 2026

When Denoising Hurts: Rethinking the Terminal Step of Diffusion Time Series Forecasters -- Extended Version

This study examines how forecast quality evolves throughout reverse diffusion to find that general temporal structure is often recovered at relatively high noise levels, whereas continued low-noise refinement can introduce statistical drift and degrade the final forecast.

Dat Nguyen-Cong, L. Tran, T. Kieu · 0 citations