mlsanityData to 14 Oct 2026

From Time Series Analysis to Question Answering: A Survey in the LLM Era

arXiv 2506.11512 ↗First posted 13 Jun 2025cs.LG cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Recently, Large Language Models (LLMs) have introduced a novel paradigm in Time Series Analysis (TSA), leveraging strong language capabilities to support tasks such as forecasting and anomaly detection. However, these analysis tasks cannot adequately cover temporal language tasks, such as interpretation and captioning. A fundamental gap remains between TSA and LLMs: LLMs are pre-trained to optimize natural language relevance for question answering rather than objectives specialized for TSA. To bridge this gap, TSA is evolving toward Time Series Question Answering (TSQA), shifting from expert-driven and task-specific analysis to user-driven and task-unified question answering. TSQA depends on flexible exploration rather than predefined TSA pipelines. In this survey, we first propose a taxonomy that reflects the evolution from TSA to TSQA, driven by a shift from external to internal alignment. We then organize existing literature into three alignment paradigms: Injective Alignment, Bridging Alignment, and Internal Alignment, and provide practical guidance for flexible, economical, and generalizable selection of alignment paradigms. We finally analyze datasets across domains and characteristics, identify challenges, and highlight future research directions.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 51 of its 70 references that are in the map. First posted on arXiv 13 Jun 2025.

Builds on

51 of 70 references.

References · 51

  1. 2024GPT-4o System Cardcited by 4,588
  2. 2023BloombergGPT: A Large Language Model for Financecited by 939
  3. 2023Large Language Modelscited by 780
  4. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 700
  5. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 500
  6. 2024Foundation Models for Time Series Analysis: A Tutorial and Surveycited by 239
  7. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 174
  8. 2022PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecastingcited by 172
  9. 2023UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecastingcited by 144
  10. 2023LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasterscited by 129
  11. 2024Large Language Models for Time Series: A Surveycited by 114
  12. 2024CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuningcited by 108
38 more
  1. 2024TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignmentcited by 103
  2. 2024ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoningcited by 103
  3. 2024ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Datacited by 100
  4. 2024Language Models Still Struggle to Zero-shot Reason about Time Seriescited by 88
  5. 2024Context is Key: A Benchmark for Forecasting with Essential Textual Informationcited by 87
  6. 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancementcited by 82
  7. 2025Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecastingcited by 63
  8. 2024LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Promptingcited by 59
  9. 2023Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Modelscited by 58
  10. 2024Deep Learning for Multivariate Time Series Imputation: A Surveycited by 57
  11. 2023ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogramcited by 54
  12. 2024Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilitiescited by 48
  13. 2024Can LLMs Understand Time Series Anomalies?cited by 41
  14. 2025TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loopcited by 39
  15. 2024ECG-Chat: A Large ECG-Language Model for Cardiac Disease Diagnosiscited by 38
  16. 2024SensorLLM: Aligning Large Language Models with Motion Sensors for Human Activity Recognitioncited by 38
  17. 2023DeWave: Discrete EEG Waves Encoding for Brain Dynamics to Text Translationcited by 36
  18. 2024A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualizationcited by 33
  19. 2024FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Modelscited by 32
  20. 2024CityGPT: Empowering Urban Spatial Cognition of Large Language Modelscited by 30
  21. 2024Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detectioncited by 29
  22. 2024Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detectioncited by 26
  23. 2024Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecastingcited by 26
  24. 2025Multi-modal Time Series Analysis: A Tutorial and Surveycited by 24
  25. 2023Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?cited by 21
  26. 2025Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillationcited by 20
  27. 2025Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Modelscited by 19
  28. 2023Integrating Stock Features and Global Information via Large Language Models for Enhanced Stock Return Predictioncited by 17
  29. 2024S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecastingcited by 17
  30. 2025Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Eracited by 12
  31. 2024MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learningcited by 11
  32. 2025Time Series Language Model for Descriptive Caption Generationcited by 11
  33. 2025SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactionscited by 11
  34. 2024TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Modelscited by 8
  35. 2025SensorQA: A Question Answering Benchmark for Daily-Life Monitoringcited by 8
  36. 2024Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classificationcited by 7
  37. 2022Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecastingcited by 3
  38. 2025Adapting Large Language Models for Time Series Modeling via a Novel Parameter-efficient Adaptation Methodcited by 3

50 most cited of 51 All 51 (JSON)

Built on by

Not cited yet.