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NVIDIA Releases Kumo Forecast, a Time-Series Model Combining Pretrained Representations with Historical Retrieval

·2026.10.21 21:51

Key point

The open-source model uses a MOMENT-1-large backbone and DARR mode to blend direct predictions with k-nearest-neighbor retrieval from historical data.

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Details

  • NVIDIA Kumo Forecast (formerly NV-Tesseract Forecasting) is a multi-variate time-series forecasting model built on the MOMENT-1-large backbone with an approximately 340-million-parameter base encoder.
  • The model introduces Domain-Aware Representation and Retrieval (DARR), a mode that combines direct Transformer predictions with patterns retrieved from historical data using a k-nearest-neighbor approach.
  • A model-agnostic interpretability framework generates horizon-specific explanations, including lag and feature attributions, without modifying the underlying forecaster.
  • The library provides a DataFrame-first API, supports input sequence lengths of 256, 512, 1024, and 2048 observations, and is available under the Apache 2.0 license.
  • Code and weights are hosted on GitHub (NVIDIA/Kumo-TS) and Hugging Face (nvidia/Kumo-Forecast), with an example provided for fine-tuning on user-supplied CSV data.
nvidiaopen-sourcetransformerforecastingtime-seriesretrieval-augmented-generation
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