mlsanityData to 7 Oct 2026

FITS: Modeling Time Series with 10k Parameters

arXiv 2307.03756 ↗First posted 6 Jul 2023cs.LGcited by 185

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Abstract (arXiv)

In this paper, we introduce FITS, a lightweight yet powerful model for time series analysis. Unlike existing models that directly process raw time-domain data, FITS operates on the principle that time series can be manipulated through interpolation in the complex frequency domain. By discarding high-frequency components with negligible impact on time series data, FITS achieves performance comparable to state-of-the-art models for time series forecasting and anomaly detection tasks, while having a remarkably compact size of only approximately 10k parameters. Such a lightweight model can be easily trained and deployed in edge devices, creating opportunities for various applications. The code is available in: urlhttps://github.com/VEWOXIC/FITS

Key facts. Cited by 185 papers in the map (data through 7 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 6 Jul 2023.

Builds on

17 of 27 references.

References · 17

  1. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  3. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  4. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  5. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  6. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  7. 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 744
  8. 2018Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholdingcited by 407
  9. 2021Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancycited by 387
  10. 2021FNet: Mixing Tokens with Fourier Transformscited by 343
  11. 2021SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interactioncited by 335
  12. 2018Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applicationscited by 223
5 more
  1. 2022Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structurescited by 158
  2. 2022FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecastingcited by 147
  3. 2022N-HiTS: Neural Hierarchical Interpolation for Time Series Forecastingcited by 146
  4. 2022ETSformer: Exponential Smoothing Transformers for Time-series Forecastingcited by 146
  5. 2022Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detectioncited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 45; 2025: 77; 2026: 59.

185 papers.

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  1. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
  2. 2024Are Language Models Actually Useful for Time Series Forecasting?cited by 163
  3. 2024DUET: Dual Clustering Enhanced Multivariate Time Series Forecastingcited by 104
  4. 2024SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameterscited by 103
  5. 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patternscited by 102
  6. 2024Frequency Adaptive Normalization For Non-stationary Time Series Forecastingcited by 45
  7. 2024Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modelingcited by 44
  8. 2024FilterNet: Harnessing Frequency Filters for Time Series Forecastingcited by 44
  9. 2024An Analysis of Linear Time Series Forecasting Modelscited by 40
  10. 2023ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizonscited by 35
  11. 2024Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicatorscited by 32
  12. 2024Scaling Law for Time Series Forecastingcited by 31
38 more
  1. 2023Mixture-of-Linear-Experts for Long-term Time Series Forecastingcited by 29
  2. 2025Temporal Query Network for Efficient Multivariate Time Series Forecastingcited by 29
  3. 2024Universal Time-Series Representation Learning: A Surveycited by 28
  4. 2025LightGTS: A Lightweight General Time Series Forecasting Modelcited by 28
  5. 2025Aurora: Towards Universal Generative Multimodal Time Series Forecastingcited by 28
  6. 2025TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecastingcited by 27
  7. 2024Hierarchical Classification Auxiliary Network for Time Series Forecastingcited by 26
  8. 2025OLinear: A Linear Model for Time Series Forecasting in Orthogonally Transformed Domaincited by 25
  9. 2023Pushing the Limits of Pre-training for Time Series Forecasting in the CloudOps Domaincited by 23
  10. 2024Learning Pattern-Specific Experts for Time Series Forecasting Under Patch-level Distribution Shiftcited by 23
  11. 2024TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Modelscited by 22
  12. 2025Time-o1: Time-Series Forecasting Needs Transformed Label Alignmentcited by 22
  13. 2023ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecastingcited by 21
  14. 2024KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networkscited by 20
  15. 2024Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecastingcited by 18
  16. 2025FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecastingcited by 18
  17. 2024Intervention-Aware Forecasting: Breaking Historical Limits from a System Perspectivecited by 16
  18. 2025PPGF: Probability Pattern-Guided Time Series Forecastingcited by 16
  19. 2025FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecastingcited by 16
  20. 2024On the Identification of Temporally Causal Representation with Instantaneous Dependencecited by 15
  21. 2025Lightweight Online Adaption for Time Series Foundation Model Forecastscited by 14
  22. 2025TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecastingcited by 11
  23. 2025Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarkscited by 10
  24. 2025FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detectioncited by 10
  25. 2025Learning with Calibration: Exploring Test-Time Computing of Spatio-Temporal Forecastingcited by 9
  26. 2024ATFNet: Adaptive Time-Frequency Ensembled Network for Long-term Time Series Forecastingcited by 8
  27. 2024MixLinear: Extreme Low Resource Multivariate Time Series Forecasting with 0.1K Parameterscited by 8
  28. 2025Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecastingcited by 8
  29. 2025CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial Correlationscited by 8
  30. 2025From Samples to Scenarios: A New Paradigm for Probabilistic Forecastingcited by 8
  31. 2025Selective Learning for Deep Time Series Forecastingcited by 8
  32. 2024On the Integration of Spatial-Temporal Knowledge: A Lightweight Approach to Atmospheric Time Series Forecastingcited by 7
  33. 2025K2VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecastingcited by 7
  34. 2025When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Seriescited by 7
  35. 2025PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecastingcited by 7
  36. 2024Not All Frequencies Are Created Equal:Towards a Dynamic Fusion of Frequencies in Time-Series Forecastingcited by 6
  37. 2025Learning General Causal Structures with Hidden Dynamic Process for Climate Analysiscited by 6
  38. 2025TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectivenesscited by 6

50 most cited of 185 All 185 (JSON)