arXiv Machine Learning August 4, 2026 By Amit Sharma, Nitin Auluck, Akramul Azim

FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting

Read the original on arXiv Machine Learning →

arXiv:2608. 01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institutionally fragmented settings, where data cannot be centralized due to regulatory, competitive, or sovereignty constraints, remains unexplored.

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