Cisco Time Series Model Technical Report

2025/11/25 by Gou, Liang, Khare, Archit, Pabolu, Praneet +10
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Forecasting Techniques and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Stock Market Forecasting Methods #Time Series Analysis and Forecasting

paper · doi:10.48550/arxiv.2511.19841

openalex publication_date 2025/11/25 · openalex created_date 2025/11/28 · openalex updated_date 2026/07/28

Abstract

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.

Citations

• Chronos-2: From Univariate to Universal Forecasting
• This Time is Different: An Observability Perspective on Time Series Foundation Models
• Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
• GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation
• Chronos: Learning the Language of Time Series
• Unified Training of Universal Time Series Forecasting Transformers
• Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
• Multi-resolution Time-Series Transformer for Long-term Forecasting
• A decoder-only foundation model for time-series forecasting
• A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
• Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
• Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Related

• TimeFound: A Foundation Model for Time Series Forecasting
• UnetTSF: A Better Performance Linear Complexity Time Series Prediction Model
• A decoder-only foundation model for time-series forecasting
• This Time is Different: An Observability Perspective on Time Series Foundation Models
• GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation