mlsanityData to 14 Oct 2026

ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data

arXiv 2412.11376 ↗First posted 16 Dec 2024cs.CL cs.LGcited by 100

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Abstract (arXiv)

Human experts typically integrate numerical and textual multimodal information to analyze time series. However, most traditional deep learning predictors rely solely on unimodal numerical data, using a fixed-length window for training and prediction on a single dataset, and cannot adapt to different scenarios. The powered pre-trained large language model has introduced new opportunities for time series analysis. Yet, existing methods are either inefficient in training, incapable of handling textual information, or lack zero-shot forecasting capability. In this paper, we innovatively model time series as a foreign language and construct ChatTime, a unified framework for time series and text processing. As an out-of-the-box multimodal time series foundation model, ChatTime provides zero-shot forecasting capability and supports bimodal input/output for both time series and text. We design a series of experiments to verify the superior performance of ChatTime across multiple tasks and scenarios, and create four multimodal datasets to address data gaps. The experimental results demonstrate the potential and utility of ChatTime.

Key facts. Cited by 100 papers in the map (data through 14 Oct 2026). Builds on 16 of its 33 references that are in the map. First posted on arXiv 16 Dec 2024.

Builds on

16 of 33 references.

References · 16

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  2. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,169
  3. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,676
  4. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,121
  5. 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,013
  6. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 632
  7. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 614
  8. 2024MOMENT: A Family of Open Time-series Foundation Modelscited by 482
  9. 2021Monash Time Series Forecasting Archivecited by 267
  10. 2024TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methodscited by 249
  11. 2024Language Models Still Struggle to Zero-shot Reason about Time Seriescited by 88
  12. 2024ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuningcited by 79
4 more
  1. 2024ChartInstruct: Instruction Tuning for Chart Comprehension and Reasoningcited by 68
  2. 2024Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmarkcited by 38
  3. 2018Deep Air Quality Forecasting Using Hybrid Deep Learning Frameworkcited by 33
  4. 2024Intervention-Aware Forecasting: Breaking Historical Limits from a System Perspectivecited by 17

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 45; 2026: 55.

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  1. 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancementcited by 82
  2. 2025Moirai 2.0: When Less Is More for Time Series Forecastingcited by 69
  3. 2025MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answeringcited by 55
  4. 2025Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrativecited by 40
  5. 2025TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loopcited by 39
  6. 2025ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Datasetcited by 37
  7. 2025OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Datacited by 36
  8. 2025TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Modelscited by 27
  9. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  10. 2025How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlookcited by 20
  11. 2025Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Seriescited by 19
  12. 2026TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Taskscited by 17
38 more
  1. 2025Out-of-Distribution Generalization in Time Series: A Surveycited by 16
  2. 2025BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Modelscited by 16
  3. 2025Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Modelscited by 15
  4. 2025Can Multimodal LLMs Perform Time Series Anomaly Detection?cited by 12
  5. 2025When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inferencecited by 12
  6. 2025BEDTime: A Unified Benchmark for Automatically Describing Time Seriescited by 12
  7. 2025TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoningcited by 12
  8. 2025When Does Multimodality Lead to Better Time Series Forecasting?cited by 11
  9. 2025Diffusion Models for Time Series Forecasting: A Surveycited by 11
  10. 2026TSAQA: Time Series Analysis Question And Answering Benchmarkcited by 11
  11. 2025Inferring Events from Time Series using Language Modelscited by 10
  12. 2025Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecastingcited by 10
  13. 2025Multimodal Conditioned Diffusive Time Series Forecastingcited by 9
  14. 2025Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedbackcited by 8
  15. 2025TRACE: Grounding Time Series in Context for Multimodal Embedding and Retrievalcited by 7
  16. 2025UniCA: Unified Covariate Adaptation for Time Series Foundation Modelcited by 7
  17. 2025DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Frameworkcited by 7
  18. 2025Text Reinforcement for Multimodal Time Series Forecastingcited by 7
  19. 2026TimeOmni-VL: Unified Models for Time Series Understanding and Generationcited by 7
  20. 2025Fusing Large Language Models with Temporal Transformers for Time Series Forecastingcited by 6
  21. 2026Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecastingcited by 6
  22. 2026ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Responsecited by 6
  23. 2025Eliciting Chain-of-Thought Reasoning for Time Series Analysis using Reinforcement Learningcited by 5
  24. 2026Overcoming the Modality Gap in Context-Aided Forecastingcited by 5
  25. 2026From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Spacecited by 5
  26. 2026Unlocking the Value of Text: Event-Driven Reasoning and Multi-Level Alignment for Time Series Forecastingcited by 5
  27. 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applicationscited by 4
  28. 2025AXIS: Explainable Time Series Anomaly Detection with Large Language Modelscited by 4
  29. 2025TsLLM: Augmenting LLMs for General Time Series Understanding and Predictioncited by 4
  30. 2026Thoth: Mid-Training Bridges LLMs to Time Series Understandingcited by 4
  31. 2025TimeSense:Making Large Language Models Proficient in Time-Series Analysiscited by 3
  32. 2026Empowering Time Series Analysis with Large-Scale Multimodal Pretrainingcited by 3
  33. 2026Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoningcited by 3
  34. 2026Towards Multimodal Time Series Anomaly Detection with Semantic Alignment and Condensed Interactioncited by 3
  35. 2026Harnessing Generalist Agents for Contextualized Time Seriescited by 3
  36. 2026Post-Training in Time Series Foundation Models: A Unifying Frameworkcited by 3
  37. 2025UniCast: A Unified Framework for Instance-Conditioned Multimodal Time-Series Forecastingcited by 2
  38. 2026TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoningcited by 2

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