mlsanityData to 7 Oct 2026

Large Language Models for Time Series: A Survey

arXiv 2402.01801 ↗First posted 2 Feb 2024cs.LG cs.AI cs.CLcited by 113

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Abstract (arXiv)

Large Language Models (LLMs) have seen significant use in domains such as natural language processing and computer vision. Going beyond text, image and graphics, LLMs present a significant potential for analysis of time series data, benefiting domains such as climate, IoT, healthcare, traffic, audio and finance. This survey paper provides an in-depth exploration and a detailed taxonomy of the various methodologies employed to harness the power of LLMs for time series analysis. We address the inherent challenge of bridging the gap between LLMs' original text data training and the numerical nature of time series data, and explore strategies for transferring and distilling knowledge from LLMs to numerical time series analysis. We detail various methodologies, including (1) direct prompting of LLMs, (2) time series quantization, (3) aligning techniques, (4) utilization of the vision modality as a bridging mechanism, and (5) the combination of LLMs with tools. Additionally, this survey offers a comprehensive overview of the existing multimodal time series and text datasets and delves into the challenges and future opportunities of this emerging field. We maintain an up-to-date Github repository which includes all the papers and datasets discussed in the survey.

Key facts. Cited by 113 papers in the map (data through 7 Oct 2026). Builds on 81 of its 97 references that are in the map. First posted on arXiv 2 Feb 2024.

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81 of 97 references.

References · 81

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38 more
  1. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
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  13. 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 492
  14. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 491
  15. 2022Transformers in Time Series: A Surveycited by 489
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 39; 2025: 45; 2026: 29.

113 papers.

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  1. 2024Language Models Still Struggle to Zero-shot Reason about Time Seriescited by 81
  2. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  3. 2024Can LLMs Understand Time Series Anomalies?cited by 41
  4. 2024Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmarkcited by 38
  5. 2024Towards Time Series Reasoning with LLMscited by 36
  6. 2024SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognitioncited by 35
  7. 2025Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrativecited by 35
  8. 2025Time Series Forecasting via Reasoning: A Slow-Thinking Approach with Reinforcement Fine-Tuned LLMscited by 34
  9. 2025TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agentscited by 33
  10. 2024Toward Foundation Model for Multivariate Wearable Sensing of Physiological Signalscited by 29
  11. 2024Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenizationcited by 26
  12. 2025Harnessing Vision Models for Time Series Analysis: A Surveycited by 26
38 more
  1. 2024Empowering Time Series Analysis with Foundation Models: A Comprehensive Surveycited by 23
  2. 2024In-context Time Series Predictorcited by 21
  3. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  4. 2025How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlookcited by 20
  5. 2025Foundation Models for Time Series: A Surveycited by 19
  6. 2024IoT-LLM: a framework for enhancing Large Language Model reasoning from real-world sensor datacited by 18
  7. 2024Evaluating Large Language Models as Virtual Annotators for Time-series Physical Sensing Datacited by 17
  8. 2024Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Taskscited by 15
  9. 2025Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Modelscited by 15
  10. 2026TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Taskscited by 15
  11. 2024Layout Agnostic Human Activity Recognition in Smart Homes through Textual Descriptions Of Sensor Triggers (TDOST)cited by 13
  12. 2024By My Eyes: Grounding Multimodal Large Language Models with Sensor Data via Visual Promptingcited by 12
  13. 2024STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysiscited by 11
  14. 2025Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Eracited by 11
  15. 2025BEDTime: A Unified Benchmark for Automatically Describing Time Seriescited by 11
  16. 2024LLaSA: A Sensor-Aware LLM for Natural Language Reasoning of Human Activity from IMU Datacited by 10
  17. 2025Time Series Analysis in Frequency Domain: A Survey of Open Challenges, Opportunities and Benchmarkscited by 10
  18. 2024StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Predictioncited by 9
  19. 2024A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classificationcited by 9
  20. 2025When Does Multimodality Lead to Better Time Series Forecasting?cited by 9
  21. 2025RETAIL: Towards Real-world Travel Planning for Large Language Modelscited by 9
  22. 2024Predicting Learning Performance with Large Language Models: A Study in Adult Literacycited by 8
  23. 2024TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Modelscited by 8
  24. 2024Financial Fine-tuning a Large Time Series Modelcited by 8
  25. 2025Multi-Modal View Enhanced Large Vision Models for Long-Term Time Series Forecastingcited by 8
  26. 2026TSAQA: Time Series Analysis Question And Answering Benchmarkcited by 8
  27. 2024DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Seriescited by 7
  28. 2025From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?cited by 7
  29. 2025CaTS-Bench: Can Language Models Describe Time Series?cited by 7
  30. 2025TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gatheringcited by 7
  31. 2024MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMscited by 6
  32. 2025CC-Time: Cross-Model and Cross-Modality Time Series Forecastingcited by 6
  33. 2024FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Modelscited by 5
  34. 2025A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysiscited by 5
  35. 2025Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingcited by 5
  36. 2025QuAnTS: Question Answering on Time Seriescited by 5
  37. 2026Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecastingcited by 5
  38. 2024UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimizationcited by 4

50 most cited of 113 All 113 (JSON)