mlsanityData to 7 Oct 2026

TimeGPT-1

arXiv 2310.03589 ↗First posted 5 Oct 2023cs.LG stat.APcited by 149

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Abstract (arXiv)

In this paper, we introduce TimeGPT, the first foundation model for time series, capable of generating accurate predictions for diverse datasets not seen during training. We evaluate our pre-trained model against established statistical, machine learning, and deep learning methods, demonstrating that TimeGPT zero-shot inference excels in performance, efficiency, and simplicity. Our study provides compelling evidence that insights from other domains of artificial intelligence can be effectively applied to time series analysis. We conclude that large-scale time series models offer an exciting opportunity to democratize access to precise predictions and reduce uncertainty by leveraging the capabilities of contemporary advancements in deep learning.

Key facts. Cited by 149 papers in the map (data through 7 Oct 2026). Builds on 19 of its 28 references that are in the map. First posted on arXiv 5 Oct 2023.

Builds on

19 of 28 references.

References · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  4. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  5. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  6. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,447
  7. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  8. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  9. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  10. 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,004
  11. 2019Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecastingcited by 748
  12. 2019N-BEATS: Neural basis expansion analysis for interpretable time series forecastingcited by 744
7 more
  1. 2020Deep Learning for Time Series Forecasting: Tutorial and Literature Surveycited by 117
  2. 2020Meta-learning framework with applications to zero-shot time-series forecastingcited by 70
  3. 2021Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSxcited by 63
  4. 2022Criteria for Classifying Forecasting Methodscited by 48
  5. 2020MQTransformer: Multi-Horizon Forecasts with Context Dependent and Feedback-Aware Attentioncited by 29
  6. 2021Probabilistic Hierarchical Forecasting with Deep Poisson Mixturescited by 16
  7. 2023Deep Learning based Forecasting: a case study from the online fashion industrycited by 12

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 57; 2025: 45; 2026: 41.

149 papers.

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  1. 2023A decoder-only foundation model for time-series forecastingcited by 650
  2. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 588
  3. 2024MOMENT: A Family of Open Time-series Foundation Modelscited by 453
  4. 2024Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Expertscited by 280
  5. 2024Timer: Generative Pre-trained Transformers Are Large Time Series Modelscited by 198
  6. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 191
  7. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 170
  8. 2024Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunitiescited by 83
  9. 2023GIVT: Generative Infinite-Vocabulary Transformerscited by 80
  10. 2024Large Scale Transfer Learning for Tabular Data via Language Modelingcited by 73
  11. 2024Empowering Time Series Analysis with Large Language Models: A Surveycited by 60
  12. 2024Scaling Wearable Foundation Modelscited by 57
38 more
  1. 2023ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputationcited by 50
  2. 2024Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilitiescited by 48
  3. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  4. 2024TimeSeriesExam: A time series understanding examcited by 47
  5. 2024Retrieval Augmented Time Series Forecastingcited by 40
  6. 2024Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoderscited by 37
  7. 2025TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecastercited by 36
  8. 2024TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Modelcited by 33
  9. 2024Scaling Law for Time Series Forecastingcited by 31
  10. 2024Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfercited by 31
  11. 2024In-Context Fine-Tuning for Time-Series Foundation Modelscited by 31
  12. 2024TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysiscited by 28
  13. 2024Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detectioncited by 26
  14. 2024TimeSeriesBench: An Industrial-Grade Benchmark for Time Series Anomaly Detection Modelscited by 22
  15. 2025MIRA: Medical Time Series Foundation Model for Real-World Health Datacited by 21
  16. 2025Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictionscited by 18
  17. 2024S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecastingcited by 17
  18. 2024Scaling-laws for Large Time-series Modelscited by 16
  19. 2024TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecastingcited by 15
  20. 2025Out-of-Distribution Generalization in Time Series: A Surveycited by 15
  21. 2024TrackGPT -- A generative pre-trained transformer for cross-domain entity trajectory forecastingcited by 13
  22. 2024Federated Foundation Models on Heterogeneous Time Seriescited by 13
  23. 2024Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series Classificationcited by 12
  24. 2025GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signalscited by 12
  25. 2025A Survey on Mathematical Reasoning and Optimization with Large Language Modelscited by 12
  26. 2024Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Predictioncited by 11
  27. 2024ViTime: Foundation Model for Time Series Forecasting Powered by Vision Intelligencecited by 11
  28. 2026Reverso: Efficient Time Series Foundation Models for Zero-shot Forecastingcited by 11
  29. 2025FeDaL: Federated Dataset Learning for General Time Series Foundation Modelscited by 10
  30. 2024A Mamba Foundation Model for Time Series Forecastingcited by 9
  31. 2026The Forecast After the Forecast: A Post-Processing Shift in Time Seriescited by 9
  32. 2024TimeGPT in Load Forecasting: A Large Time Series Model Perspectivecited by 8
  33. 2024Financial Fine-tuning a Large Time Series Modelcited by 8
  34. 2025There are no Champions in Supervised Long-Term Time Series Forecastingcited by 8
  35. 2025Synapse: Adaptive Arbitration of Complementary Expertise in Time Series Foundational Modelscited by 7
  36. 2023Large Scale Foundation Models for Intelligent Manufacturing Applications: A Surveycited by 6
  37. 2024CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecastingcited by 6
  38. 2024Macroeconomic Forecasting with Large Language Modelscited by 6

50 most cited of 149 All 149 (JSON)