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Cisco Time Series Model Technical Report

arXiv 2511.19841 ↗First posted 25 Nov 2025cs.LG cs.AI stat.MLcited by 0

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Abstract (arXiv)

We introduce the Cisco Time Series Model, a univariate zero-shot forecaster. This time series foundation model is the result of a general architectural innovation to a time series model enabling it to accept multiresolution input, applied to a popular decoder-only time series model (TimesFM). The resulting multiresolution decoder-only model is trained on over 300B unique data points, with more than half coming from the observability domain. Quantitative and qualitative evaluations demonstrate that the resulting model achieves superior performance on observability datasets while retaining very similar performance on a standard general-purpose forecasting benchmark (GIFT-Eval), and suggest that the multiresolution structure enables the model to make more accurate predictions on long context input.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 17 references that are in the map. First posted on arXiv 25 Nov 2025.

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References · 12

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  3. 2024Chronos: Learning the Language of Time Seriescited by 759
  4. 2023A decoder-only foundation model for time-series forecastingcited by 692
  5. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 614
  6. 2024GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluationcited by 212
  7. 2025Chronos-2: From Univariate to Universal Forecastingcited by 194
  8. 2024Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecastingcited by 104
  9. 2024Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Expertscited by 95
  10. 2025This Time is Different: An Observability Perspective on Time Series Foundation Modelscited by 68
  11. 2022Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecastingcited by 54
  12. 2023Multi-resolution Time-Series Transformer for Long-term Forecastingcited by 41

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