mlsanityData to 14 Oct 2026

MoTime: A Dataset Suite for Multimodal Time Series Forecasting

arXiv 2505.15072 ↗First posted 21 May 2025cs.LG cs.CL cs.DBcited by 7

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Abstract (arXiv)

While multimodal data sources are increasingly available from real-world forecasting, most existing research remains on unimodal time series. In this work, we present MoTime, a suite of multimodal time series forecasting datasets that pair temporal signals with external modalities such as text, metadata, and images. Covering diverse domains, MoTime supports structured evaluation of modality utility under two scenarios: 1) the common forecasting task, where varying-length history is available, and 2) cold-start forecasting, where no historical data is available. Experiments show that external modalities can improve forecasting performance in both scenarios, with particularly strong benefits for short series in some datasets, though the impact varies depending on data characteristics. By making datasets and findings publicly available, we aim to support more comprehensive and realistic benchmarks in future multimodal time series forecasting research.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 35 of its 57 references that are in the map. First posted on arXiv 21 May 2025.

Builds on

35 of 57 references.

References · 35

  1. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,169
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  3. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,424
  4. 2024Chronos: Learning the Language of Time Seriescited by 759
  5. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 700
  6. 2023A decoder-only foundation model for time-series forecastingcited by 692
  7. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 614
  8. 2024Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Expertscited by 287
  9. 2024MT-Bench-101: A Fine-Grained Benchmark for Evaluating Large Language Models in Multi-Turn Dialoguescited by 250
  10. 2024Foundation Models for Time Series Analysis: A Tutorial and Surveycited by 239
  11. 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 224
  12. 2024GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluationcited by 212
23 more
  1. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 197
  2. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 174
  3. 2023TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Seriescited by 169
  4. 2023LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasterscited by 129
  5. 2024Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Seriescited by 127
  6. 2023Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecastingcited by 113
  7. 2024From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflectioncited by 98
  8. 2024Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Expertscited by 95
  9. 2024Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysiscited by 74
  10. 2023Frozen Language Model Helps ECG Zero-Shot Learningcited by 62
  11. 2024LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Promptingcited by 59
  12. 2023DreamDiffusion: Generating High-Quality Images from Brain EEG Signalscited by 56
  13. 2024Toto: Time Series Optimized Transformer for Observabilitycited by 48
  14. 2023An Image Dataset for Benchmarking Recommender Systems with Raw Pixelscited by 18
  15. 2021Well Googled is Half Done: Multimodal Forecasting of New Fashion Product Sales with Image-based Google Trendscited by 15
  16. 2018Multi-Source Social Feedback of Online News Feedscited by 14
  17. 2023Multi-Modal Financial Time-Series Retrieval Through Latent Space Projectionscited by 8
  18. 2022Multimodal Quasi-AutoRegression: Forecasting the visual popularity of new fashion productscited by 6
  19. 2025Unveiling the Potential of Text in High-Dimensional Time Series Forecastingcited by 4
  20. 2022Community Trend Prediction on Heterogeneous Graph in E-commercecited by 3
  21. 2022The multi-modal universe of fast-fashion: the Visuelle 2.0 benchmarkcited by 3
  22. 2024Scalable Transformer for High Dimensional Multivariate Time Series Forecastingcited by 3
  23. 2025Dual-Forecaster: A Multimodal Time Series Model Integrating Descriptive and Predictive Textscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  2. 2026Rethinking Multimodal Time-Series Forecasting Evaluationcited by 7
  3. 2025QuAnTS: Question Answering on Time Seriescited by 5
  4. 2025UniDiff: A Unified Diffusion Framework for Multimodal Time Series Forecastingcited by 1
  5. 2026TimeBraid: Unifying Time Series and Language for Understanding and Forecastingcited by 0
  6. 2026GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluationcited by 0
  7. 2026MMTA: Benchmarking Multimodal Temporal Analysis with Time Series, Text, and Visioncited by 0