mlsanityData to 7 Oct 2026

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis

arXiv 2410.04047 ↗First posted 5 Oct 2024cs.LG cs.AIcited by 28

On the map: LLM reasoning → Time series reasoning

also in 1 more
Abstract (arXiv)

Time series analysis is crucial in real-world applications, yet traditional methods focus on isolated tasks only, and recent studies on time series reasoning remain limited to either single-step inference or are constrained to natural language answers. In this work, we introduce TS-Reasoner, a domain-specialized agent designed for multi-step time series inference. By integrating large language model (LLM) reasoning with domain-specific computational tools and an error feedback loop, TS-Reasoner enables domain-informed, constraint-aware analytical workflows that combine symbolic reasoning with precise numerical analysis. We assess the system's capabilities along two axes: (1) fundamental time series understanding assessed by TimeSeriesExam and (2) complex, multi-step inference evaluated by a newly proposed dataset designed to test both compositional reasoning and computational precision in time series analysis. Experiments show that our approach outperforms standalone general-purpose LLMs in both basic time series concept understanding as well as the multi-step time series inference task, highlighting the promise of domain-specialized agents for automating real-world time series reasoning and analysis.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Placed in Time series reasoning, one of 17 directions in LLM reasoning. Builds on 47 of its 74 references that are in the map. First posted on arXiv 5 Oct 2024.

Builds on

47 of 74 references.

References · 47

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  5. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  6. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  7. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,628
  8. 2024Chronos: Learning the Language of Time Seriescited by 712
  9. 2023Time-LLM: Time Series Forecasting by Reprogramming Large Language Modelscited by 680
  10. 2022PAL: Program-aided Language Modelscited by 635
  11. 2022Towards Reasoning in Large Language Models: A Surveycited by 593
  12. 2024Unified Training of Universal Time Series Forecasting Transformerscited by 588
35 more
  1. 2021CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputationcited by 577
  2. 2018Deep learning for time series classification: a reviewcited by 575
  3. 2022Decomposed Prompting: A Modular Approach for Solving Complex Taskscited by 554
  4. 2024Executable Code Actions Elicit Better LLM Agentscited by 537
  5. 2022Visual Programming: Compositional visual reasoning without trainingcited by 507
  6. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 491
  7. 2020Time Series Forecasting With Deep Learning: A Surveycited by 457
  8. 2024MOMENT: A Family of Open Time-series Foundation Modelscited by 453
  9. 2021Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancycited by 387
  10. 2023Evaluating Large Language Models at Evaluating Instruction Followingcited by 290
  11. 2024Large Language Models for Mathematical Reasoning: Progresses and Challengescited by 283
  12. 2024Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Expertscited by 280
  13. 2022Reasoning with Language Model Prompting: A Surveycited by 251
  14. 2023AdaPlanner: Adaptive Planning from Feedback with Language Modelscited by 193
  15. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 170
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  17. 2024Recursive Introspection: Teaching Language Model Agents How to Self-Improvecited by 162
  18. 2023TimeGPT-1cited by 149
  19. 2023TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecastingcited by 136
  20. 2022Faithful Reasoning Using Large Language Modelscited by 130
  21. 2022Deep Learning for Time Series Anomaly Detection: A Surveycited by 130
  22. 2024AgentScope: A Flexible yet Robust Multi-Agent Platformcited by 120
  23. 2024From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflectioncited by 93
  24. 2024Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models -- A Surveycited by 82
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 22.

28 papers.

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  1. 2026Auditing Multi-Agent LLM Reasoning Trees Outperforms Majority Vote and LLM-as-Judgecited by 16
  2. 2026TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Taskscited by 15
  3. 2025Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMscited by 14
  4. 2026POET: Power-Oriented Evolutionary Tuning for LLM-Based RTL PPA Optimizationcited by 11
  5. 2026Adaptive Collaboration with Humans: Metacognitive Policy Optimization for Multi-Agent LLMs with Continual Learningcited by 9
  6. 2025TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gatheringcited by 7
  7. 2025Structured Spectral Reasoning for Frequency-Adaptive Multimodal Recommendationcited by 6
  8. 2025Foundation Models for Demand Forecasting via Dual-Strategy Ensemblingcited by 5
  9. 2026TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scalecited by 5
  10. 2026RaMem: Contextual Reinstatement for Long-term Agentic Memorycited by 5
  11. 2025Training-Free Time Series Classification via In-Context Reasoning with LLM Agentscited by 4
  12. 2026KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoningcited by 4
16 more
  1. 2025A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMscited by 3
  2. 2026Bridging the Last Mile of Time Series Forecasting with LLM Agentscited by 3
  3. 2026Geometry over Density: Few-Shot Cross-Domain OOD Detectioncited by 2
  4. 2026TimeClaw: A Time-Series AI Agent with Exploratory Execution Learningcited by 2
  5. 2026De-conflating Preference and Qualification: Constrained Dual-Perspective Reasoning for Job Recommendation with Large Language Modelscited by 1
  6. 2026AION: Next-Generation Tasks and Practical Harness for Time Seriescited by 1
  7. 2026From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligencecited by 1
  8. 2026LLM Agents for Time-Series: A Surveycited by 1
  9. 2026VLM4Rec: Multimodal Semantic Representation for Recommendation with Large Vision-Language Modelscited by 0
  10. 2026Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecastingcited by 0
  11. 2026Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systemscited by 0
  12. 2026When Text and Numbers Disagree: Evidence Arbitration in Large Language Modelscited by 0
  13. 2026TraceBench: Controlled Evaluation of LLM Agents for Time-Series Root-Cause Attributioncited by 0
  14. 2026TimeEvo: Failure-Driven Self-Evolution of a Time Series Agentcited by 0
  15. 2026Controlled Decoding Attacks on Black-Box LLMscited by 0
  16. 2026OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoning
  2. 2025Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision
  3. 2025TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
  4. 2025Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
  5. 2026TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning
  6. 2025When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
  7. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
  8. 2026From Recognition to Understanding: Unlocking Cognitive Time Series Reasoning with LLMs