mlsanityData to 7 Oct 2026

Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision

arXiv 2510.16980 ↗First posted 19 Oct 2025cs.LGcited by 2

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Abstract (arXiv)

Time series reasoning is emerging as the next frontier in temporal analysis, aiming to move beyond pattern recognition towards explicit, interpretable, and trustworthy inference. This paper presents a BlueSky vision built on two complementary directions. One builds robust foundations for time series reasoning, centered on comprehensive temporal understanding, structured multi-step reasoning, and faithful evaluation frameworks. The other advances system-level reasoning, moving beyond language-only explanations by incorporating multi-agent collaboration, multi-modal context, and retrieval-augmented approaches. Together, these directions outline a flexible and extensible framework for advancing time series reasoning, aiming to deliver interpretable and trustworthy temporal intelligence across diverse domains.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 39 of its 57 references that are in the map. First posted on arXiv 19 Oct 2025.

Builds on

39 of 57 references.

References · 39

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,141
  3. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 1,981
  4. 2021Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecastingcited by 1,654
  5. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,400
  6. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
  7. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,030
  8. 2017Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networkscited by 869
  9. 2025Emerging Properties in Unified Multimodal Pretrainingcited by 855
  10. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 680
  11. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 491
  12. 2022Non-stationary Transformers: Exploring the Stationarity in Time Series Forecastingcited by 385
27 more
  1. 2017A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Predictioncited by 245
  2. 2024Foundation Models for Time Series Analysis: A Tutorial and Surveycited by 234
  3. 2025Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Toolscited by 106
  4. 2024ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoningcited by 95
  5. 2024Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoningcited by 83
  6. 2024Language Models Still Struggle to Zero-shot Reason about Time Seriescited by 81
  7. 2022Spatio-Temporal Self-Supervised Learning for Traffic Flow Predictioncited by 77
  8. 2025Time-MQA: Time Series Multi-Task Question Answering with Context Enhancementcited by 74
  9. 2024Causal machine learning for predicting treatment outcomescited by 73
  10. 2024Empowering Time Series Analysis with Large Language Models: A Surveycited by 60
  11. 2021Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Networkcited by 52
  12. 2025MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answeringcited by 50
  13. 2025TimeXL: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loopcited by 39
  14. 2024Towards Time Series Reasoning with LLMscited by 36
  15. 2025TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecastercited by 36
  16. 2025Time Series Forecasting via Reasoning: A Slow-Thinking Approach with Reinforcement Fine-Tuned LLMscited by 34
  17. 2025TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agentscited by 33
  18. 2024A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualizationcited by 31
  19. 2025Harnessing Vision Models for Time Series Analysis: A Surveycited by 26
  20. 2025Multi-modal Time Series Analysis: A Tutorial and Surveycited by 24
  21. 2025Time-R1: Towards Comprehensive Temporal Reasoning in LLMscited by 23
  22. 2024Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotationcited by 21
  23. 2025Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecastingcited by 19
  24. 2025PPGF: Probability Pattern-Guided Time Series Forecastingcited by 16
  25. 2025TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learningcited by 16
  26. 2019Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detectioncited by 13
  27. 2023Deep Learning for Energy Time-Series Analysis and Forecastingcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learningcited by 7
  2. 2026Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
  2. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
  3. 2026Visual Reasoning over Time Series via Multi-Agent System
  4. 2025Towards Interpretable Time Series Foundation Models
  5. 2026From Recognition to Understanding: Unlocking Cognitive Time Series Reasoning with LLMs
  6. 2024TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
  7. 2026KairosVL: Orchestrating Time Series and Semantics for Unified Reasoning
  8. 2025TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering